A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ... · Broadening Participation Cluster 45...

A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)


Women, Youth and Persons with Disabilities


Research report prepared for the Department of Women, Youth and Persons with Disabilities by the Development Policy Research Unit, University of Cape Town

December 2018



Table of ConTenTsHigH level sUmmaRY i

exeCUTive sUmmaRY iii

1. inTRoDUCTion 1

2. Women’s eConomiC PaRTiCiPaTion 3

2.1. Conceptualising Women’s Economic Participation 3

2.2. The Role of the dti in Promoting Women’s Economic Participation 7

3. Women’s eConomiC PaRTiCiPaTion in soUTH afRiCa 9

3.1. The Labour Market Context 9

3.1.1. Overview of the Labour Market 9

3.1.2. Labour Force Participation 10

3.1.3. Employment 13

3.1.3.1. Employment by industry 13

3.1.3.2. Skills distribution of employment 14

3.1.3.3. Formality and informality 16

3.1.4. Women in Self-Employment 17

3.1.5. Unemployment 24

3.2. Constraints to SMME Growth and Entrepreneurship in South Africa 26

4. inCenTive PRogRammes as a PoliCY insTRUmenT 30

4.1. Review of Selected International Incentive Programmes 30

4.1.1. Country Contexts 30

4.1.2. Chile 32

4.1.2.1. Women-Specific Initiatives 32

4.1.2.2. Other Relevant Initiatives 33

4.1.2.3. Summary 34

4.1.3. Ethiopia 34



4.1.3.3. Summary 36


4.1.4. Germany 36



4.1.4.3. Summary 38

4.1.5. Thailand 38



4.1.5.3. Summary 40

4.2. The dti’s Incentive Programmes 40

4.2.1. The dti’s Approach to Incentives 40

4.2.2. Overview of the dti Incentive Schemes 45

4.2.2.1. Broadening Participation Cluster 45

4.2.2.2. Manufacturing Investment Cluster 46

4.2.2.3. Services Investment Cluster 48

4.2.2.4. Competitiveness Investment Cluster 50

4.2.2.5. Infrastructure Investment Cluster 55

4.2.3. dti Programmes with a Particular Focus on Women 57

4.3. Summary 59

5. DaTa To sUPPoRT THe genDeR analYsis of inCenTive PRogRammes 60

5.1. Data Quality 60

5.2. Existing Data Limitations 64

5.2.1. Data collection, entry and follow-up 64

5.2.2. Access to data and authority to use and share data 65

5.3. The Importance of Data within the Context of Government’s M&E System 65

5.4. Summary 71

6. analYsis of THe seCToR-sPeCifiC assisTanCe sCHeme (ssas) 73

6.1. SSAS Overview 73

6.1.1. Overview of the programme 73

6.1.2. How SSAS is thought to impact firm outcomes 74



6.1.3. The application process and project coordinators 76

6.1.4. Qualifying sectors 79

6.1.5. Measuring impact 80

6.2. Women in the SSAS-Eligible Subsectors 81

6.3. Survey Results 84

6.3.1. Methodology 84

6.3.1.1. Background 84

6.3.1.2. Demographic and Labour Market Characteristics across Sampled SSAS Subsectors 84

6.3.1.3. Sample Characteristics 87

6.3.2. Results and Discussion 88

6.3.2.1. The Application Process 88

6.3.2.2. Quality of Support Received 91

6.3.3. Impact of the SSAS 94

7. finDings 103

7.1. Main Findings 103

7.1.1. Gender Dynamics within the Broader Labour Market 103

7.1.2. Incentive Programmes as a Policy Instrument 105

7.1.3. SSAS Case Study 107

7.2. Incorporating Considerations of Gender into Gender-Blind Incentive Schemes 111

8. ConClUsion anD ReCommenDaTions 115

9. RefeRenCes 119

aPPenDix i: DaTa 126

aPPenDix ii: aDDiTional figURes 128

aPPenDix iii: aDDiTional Tables 129

aPPenDix iv: sURveY of ssas benefiCiaRies 132


lisT of figUResFigure 1. Conceptualising economic participation through a labour market lens 4

Figure 2. Labour force participation rates by gender, 2016-2018 11

Figure 3. Labour force participation by gender, various countries, 2017 12

Figure 4. Distribution of employment across industry by gender, 2016 14

Figure 5. Educational attainment of employed women by youth status, 2016 16

Figure 6. Educational attainment of self-employed women by youth status, 2013 and 2016 20

Figure 7. Main source of own money for business funding by gender, 2013 23

Figure 8. Female labour force, employment and unemployment shares, 2008-2018 25

Figure 9. Narrow unemployment rates by gender, 2018 26

Figure 10. IDAD incentives budget, 2012/13-2016/17 41

Figure 11. IDAD incentive structure, 2015/16 and 2016/17 42

Figure 12. IDAD overview, 2012/13 to 2016/17 43

Figure 13. IDAD approvals, by number and value, 2016/17 43

Figure 14. Projected investment ratio and projected incentive cost per new job, 2016/17 44

Figure 15. THRIP outcomes, 2002-2013 46

Figure 16. BPS jobs supported, 2013/14-2016/17 49

Figure 17. EMIA approvals by sub-sector, 2016/17 52

Figure 18. Women-owned firms’ perceptions on EMIA 53

Figure 19. SSAS approvals and disbursements, 2011/12-2016/17 54

Figure 20. SSAS approvals by subsector, 2016/17 55

Figure 21. CIP projected investment, projected jobs and disbursements, 2011/12-2016/17 57

Figure 22. Women-focussed programmes budget, 2015/16-2016/17 58

Figure 23. A conceptual framework of data quality 60

Figure 24. Data quality framework 61

Figure 25. Illustrative example of an M&E process incorporating gender 69



Figure 26. SSAS process from the perspective of applicants 75

Figure 27. SSAS project coordinators by number of approvals, 2017/18 78

Figure 28. Distribution of firms by number of approvals received, 2015/16-2016/17 79

Figure 29. Sectoral project approvals by project coordinator, 2017/18 80

Figure 30. Distribution of employment across SSAS-eligible subsectors, 2016 81

Figure 31. Female share of employment across SSAS subsectors, 2016 82

Figure 32. Gender ratio in employment by race across SSAS-eligible subsectors, 2016 83

Figure 33. Skills and gender distribution of workers in selected SSAS subsectors, 2016 86

Figure 34. Where did respondents first hear of the SSAS? 89

Figure 35. Number of employees before and after participation in the SSAS 99

Figure 36. Number of employees pre- and post-SSAS participation, by gender 100


lisT of TablesTable 1. Mean time spent in market and home production by gender in South Africa (hours per day) 6

Table 2. Labour market statistics by gender, 2016 and 2018Q2 9

Table 3. Labour force participation rates by gender and location, 2018 12

Table 4. Distribution of employed women across industry by skills category, 2016 15

Table 5. Employment by sector, 2016 17

Table 6. Registration status of enterprises of the self-employed, 2016 18

Table 7. Self-employment rates by race and gender, 2013 and 2016 19

Table 8. Occupational distribution of self-employed women, 2013 and 2016 20

Table 9. Distribution of self-employed women across industry, 2013 and 2016 21

Table 10. Self-employment type by gender, 2013 21

Table 11. Employees of male and female informal employers, 2013 22

Table 12. Main source of business funding by gender, 2013 23

Table 13. Reasons for non-registration of business by gender, 2013 24

Table 14. Share of 18-64 year olds engaged in entrepreneurial activity, by region 28

Table 15. Barriers to credit for women and their effects 29

Table 16. Key indicators for Chile, Ethiopia, Germany, Thailand and South Africa, 2017 31

Table 17. The Broadening Participation Cluster, 2016/17 45

Table 18. Manufacturing Investment Cluster, 2016/17 47

Table 19. Services Investment Cluster, 2016/17 49

Table 20. Competitiveness Investment Cluster, 2016/17 50

Table 21. EMIA approvals, 2013/14-2016/17 51

Table 22. EMIA approvals by firm characteristics, 2014/15 and 2016/17 53

Table 23. Infrastructure Investment Cluster, 2016/17 56

Table 24. Data quality dimensions 63

Table 25. Components of the outcomes-based approach to M&E and the relevant data requirements 67

Table 26. Educational attainment of workers in selected SSAS subsectors, 2016 85

Table 27. Gender and age distribution of employment across selected SSAS subsectors, 2016 86

Table 28. Baseline summary statistics of interviewed firms, 2018 87

Table 29. When did the business apply for SSAS support? 88

Table 30. Change in export share and turnover pre- and post-SSAS participation 95

Table 31. Number of leads and conversions into sales 95

Table 32. Firms’ turnover at application for the SSAS and for most recent period 97

iA GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)


HigH level sUmmaRYAn environment that empowers women to effectively engage in the labour market and be productive is essential to eliminate

the various economic and social inequalities that exist between men and women. Importantly, allowing women to take up

productive employment helps ensure that society more broadly can directly reap some of the benefits of the investment in

women.

The challenges women face in fully accessing the labour market include differentials in educational attainment and quality;

interruption of labour force participation related to childbearing; discrimination in terms of employment practices and wage

determination; relatively fewer role models; vulnerability and weak bargaining power; and environments that may be hostile

to female membership of the workforce. Women typically also face the consequences of gender norms and the unequal

division of labour.

This report aims to provide insights into three key questions, namely:

i. How are women currently accessing incentives offered by the dti?

ii. What impact do these incentives have on women?

iii. Do the incentives adequately target and make provision for women within the process?

The quantitative and qualitative work revealed the following findings about women in the labour market and the role of

incentives in facilitating the economic inclusion of women:

a. There are important gender differences in the South African labour market.

b. Among women themselves however, there are also important differences in the labour market by race, therefore the

intersection of marginalised identities cannot be ignored.

c. Access to credit as a constraint for SMMEs is exacerbated for women due to traditional norms which feed adverse

attitudes towards women, exclude women from financial and economic decision making and from accumulating

assets and property.

d. South Africa can learn ways in which to best support entrepreneurs from international incentive schemes. Schemes

specifically designated for female entrepreneurs will attract and retain females, thus increasing overall participation

and lowering poverty and inequality. This necessitates a well-coordinated policy strategy, with collaboration across

different government departments, levels of government and relevant external organisations.

e. While IDAD administers and manages a number of incentive schemes targeting different enterprises, these are not

targeted to women in particular.

f. Data related to female beneficiaries in particular is only collected for three of the IDAD incentive schemes.

g. High quality data should be collected to enable effective M&E of government programmes. Lack of data, as well as

poor quality data, places limitations on the types of evaluations and analysis which can be conducted in respect of

government programmes.

h. The SSAS application process is generally straightforward for all applicants although there is some concern about the

potential for gatekeeping by the project coordinators.

i. Measures of success for the SSAS programme do not currently include gender as an aspect of consideration.

j. There may be need for gender-specific support for SSAS beneficiaries.

k. While the impact of the SSAS may be through many channels, improvements cannot necessarily be tied to the SSAS.

ii A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)

l. All but one of the firm saw increased turnover after receiving the SSAS support. While this cannot be directly linked to

the SSAS support, it is clear that SSAS is well-targeted at growing rather than declining firms.

m. Five firms saw a positive shift in their profitability from the pre-SSAS period to the post-SSAS period.

n. Three-quarter of the firms planned to expand and more than half of these firms indicated that the SSAS support they

received contributed to this decision.

o. Experience and learning can be impactful, if harder to measure.

p. Around half of firms reported an increase in the number of female employees in the most recent period after attending

an export show, although these employment changes cannot necessarily be tied to the SSAS support received.

q. Impact in terms of greater procurement from female-owned businesses appeared to be limited, suggesting a further

channel through which women can be empowered through such incentives that is not currently being used to its full

potential.

Recommendations

Ia. If government is serious about properly measuring and monitoring the performance and impact of incentive schemes,

the collection of relevant data must be prioritised.

Ib. Data collection for the purposes of measuring performance and impact of incentive schemes should be integrated into

the design of the scheme to ensure accuracy and completeness.

II. Women’s access to incentive programmes should be prioritised in order to effectively help address their historical and

continuing economic marginalisation.

IIIa. To promote women’s fuller economic participation, incentive programmes and other types of support cannot ignore

those in the informal sector or those in rural areas or smaller urban centres.

IIIb. Where providing support to the informal sector is not feasible, for whatever reason, policy should focus on making

formalisation both an attractive option and a relatively straightforward process.

IV. The dti should monitor impact in terms of gender as a standard feature of evaluations of their interventions.

V. While assessments of incentive schemes and other similar interventions are economic in nature, it is worth trying

to understand their impact in terms that are not purely economic but which may in turn have important effects on

outcomes.

VI. The SSAS may need tailoring to account for the specific challenges faced by women and women-owned firms.

VII. South Africa should remain open to learning from the experiences of other countries and adapt policy where necessary.

iiiA GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)


exeCUTive sUmmaRYThe centrality of the labour market to women’s ability to interact with the broader economy should not be understated. An

environment that empowers women to effectively engage in the labour market and be productive is essential to eliminate

some of the various economic and social inequalities that exist between men and women. Importantly, allowing women

to take up productive employment helps ensure that society more broadly can directly reap some of the benefits of the

investment in women.

Globally, women face significant challenges in the labour market and South Africa is no different. These challenges include

differentials in educational attainment and quality; interruption of labour force participation related to childbearing;

discrimination in terms of employment practices and wage determination; relatively fewer role models; vulnerability and weak

bargaining power; and environments that may be hostile to female membership of the workforce. Women typically also face

the consequences of gender norms and the unequal division of labour. This is due to women being seen as caregivers within

the family, while men are viewed as bread-winners.

Given these challenges, an outcome of various programmes undertaken by the Department of Women (DoW) is to ensure

the financial inclusion and support of women so that they can fully participate in the economy. Participation in the formal

sector holds the promise of higher incomes. Access to funding for women should not be underestimated due to its role

in securing the empowerment and advancement of women in the economy. In this regard, the DoW has identified the

incentives supervised by the Department of Trade and Industry (the dti) as the focus of this research.

The research need emanates from the DoW’s acknowledgment that women often struggle to access services, especially

those related to access to markets and funding, that the dti offers. Considering this, the DoW requested a gender analysis

of the services of the dti to determine whether women benefit from its services and funding and what the impacts of these

interventions are. This research therefore takes the form of a gendered analysis of the dti’s services and funding process. In

order to do this, we undertake a quantitative analysis into the position of women within the South African economy as well

as an overview of the dti incentive programmes and the extent to which they currently benefit women. We also undertake a

qualitative case study into the Sector Specific Incentive Scheme (SSAS) and use this as a guide into how incentives should be

structured and implemented so that female participants can derive the maximum benefit from the given intervention.

Overall, this report aims to provide insights into three key questions related to how women have benefitted from and can best

benefit from incentives offered by the dti:

I. How are women currently accessing incentives offered by the dti?

II. What impact do these incentives have on women, both directly (that is, through the impact on the beneficiary’s

business) as well as indirectly (that is, through the increased employment and procurement from other women

because of the incentive)?

III. Do the incentives adequately target and make provision for women within the process – from the application

process to the outcome? Ultimately this would indicate whether a gender-specific stream of the incentive is

necessary or whether a new incentive specifically targeted toward women would be more appropriate in the case

of the incentive under consideration?

iv A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)

Conceptualising Women’s Economic Participation

Barriers to Female Participation in the Labour Market

For the purposes of this research, we consider women’s economic participation from the perspective of the labour market

only and exclude aspects of participation related to their roles as consumers. Women’s participation in the labour market

encompasses a number of elements that begin with the decision to seek work and thus participate in the labour market

through to the financial and other outcomes associated with the employment they ultimately obtain. These processes,

broadly, can be classified as the following: (i) the decision to participate in the labour market; (ii) employment status in the

labour market; and (iii) the nature of employment (which in turn affects the ultimate financial result associated with the type

of participation in the labour market and economy).

We begin with the decision to participate in the labour market. Here, the term ‘decision’ should not be conflated with the

idea of ‘choice’, since there are many instances where women do not have free choice on whether or not to participate. The

decision to participate is influenced by a variety of factors that operate at the individual, household or societal level. Some of

these factors are discussed in greater detail below, but may include the woman’s own preferences, her family circumstances,

or social norms around women working outside the home. The interplay of these and other factors together will determine

a country’s specific female labour force participation rate. Women who decide not to participate in the labour market—for

example, those engaged in tertiary education, those who remain at home, or those who are ill—are termed not economically

active.

Once counted among those in the labour force, a woman will either find employment or remain unemployed. Labour force

participants who are without work but are willing and able to work and are actively seeking employment, are considered

to be unemployed according to the narrow definition of unemployment. Participants without employment who have not

taken active steps to find (or create their own) employment but who would work if offered employment, are defined as non-

searching unemployed (also referred to as discouraged work seekers). The broad definition of unemployment includes the

non-searching unemployed as part of the unemployed and, consequently, the labour force. Whether a woman finds work or is

unemployed (as well as whether or not she actively searches for work) is also affected by various individual and societal factors.

Together, these factors will determine the female unemployment rate.

Women who find work may be employed in various sectors and occupations; they may also be employed in either the formal

sector or the informal sector. They may be hired by another individual or a firm and thus be classified as an employee, or they

may choose (or be forced into) self-employment. If they are self-employed, they may be working alone or be an employer

themselves. Irrespective of these modalities of employment, for all the employed, variation exists across employment

outcomes. These include remuneration, working conditions, protections and benefits, flexibility and so on. Again, the exact

nature of employment and the associated employment outcomes are affected by various individual and societal factors.

Individual-level labour market outcomes—economic inactivity, unemployment or employment as mediated through

employment outcomes—play an important role in determining wellbeing at the individual and household level, as well as

influencing aspects such as income distribution at the societal level. At the same time, household, societal and macroeconomic

factors all influence the ultimate wellbeing outcome directly, as well as indirectly through their influences on decisions to

participate and the likelihood of finding employment. Indeed, wellbeing itself may influence the decision to participate.

Aside from income level and economic structure, the International Labour Office (2010) identify some of the most important

determinants of female labour force participation as: fertility; education; cultural and social norms, including religion;

institutions such as government policy, legal frameworks, and unions; political regimes; and the existence of violent conflict.

vA GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)


The Role of the dti in Promoting Women’s Economic Participation

Given challenges faced by women in the economy, an outcome of various programmes undertaken by the Department of

Women (DoW) is to ensure the financial inclusion and support of women so that they can fully participate in the economy.

Participation in the formal sector holds the promise of higher incomes. Access to funding for women should not be

underestimated in its role in the empowerment and advancement of women in the economy.

While the dti cannot directly affect such factors as fertility, cultural norms and household influences that have an effect on the

participation of women in the economy, it can provide incentive funding to assist women to improve their financial positions

and through doing this create an enabling environment for women’s participation in the economy by taking the specific

challenges that women face into consideration in designing incentives and by targeting women in particular.

In this report, we focus specifically on how the dti incentives can influence participation in the economy and improve the

inclusion of women in the economy through its incentives that focus on expanding South African businesses.

In terms of participation, in line with the outline of labour market participation above, the dti can have an impact on either of

the components of women’s participation in the economy listed above through the incentives it offers:

i. It can influence the decision to participate in the labour market by empowering women in a manner that changes

cultural norms that may be limiting participation currently: a more representative economy will go some way towards

changing norms that currently restrict women’s participation in the economy.

ii. It can increase the likelihood of finding employment for women through investing in programmes that encourage

growth of businesses owned by women and employment of women through the support of such business growth.

iii. It can contribute toward the types of employment and, specifically, self-employment opportunities available to

women.

Because dti incentives are aimed at assisting businesses to grow, they will have a direct effect on women’s participa-tion in the labour market in respect of self-employment primarily through the support of women-owned businesses. We will thus focus on this aspect of how dti incentives can impact on women’s participation in the economy in this report.

Women’s Economic Participation in South Africa

Overview of the Labour Market: Employment and Labour Force Participation

There are important gender differences in the South African labour market. Men form the majority of those with better labour

market outcomes (employment as opposed to unemployment) and women dominate amongst those with worse labour

market outcomes (non-searching unemployment as opposed to narrow unemployment). Further, while participation of both

men and women in the labour market is low relative to other developing countries, participation of women in the labour

market is lower than that of men.

Gender differences extend beyond high-level labour market outcomes and are observable in various areas of employment.

Female employment is concentrated in four industries: community, social and personal (CSP) services; wholesale and retail

trade; private households; and finance. Women dominate employment in only two industries: CSP services, which includes

government, and private households, which is primarily domestic work. In contrast, construction, mining and transport are

heavily male dominated. Males are more likely than females to be employed in both the formal sector and in the informal

sector. In contrast, private households account for 14.3 percent of female employment, more than four times the share for

males.

vi A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)

Among women themselves, there are also important differences. By race, labour force participation rates are more varied

for women than for men. The labour force participation gap between men and women is highest for Whites and Asians.

Participation rates for women range from 45.5 percent amongst Asian women to 58.3 percent amongst Coloured women.

African women constitute a relatively large proportion of female employment in the informal sector and in private households

compared with their share of total female employment. In rural areas women (as well as men) are much less likely to be

economically active.

Women in Self-Employment

In self-employment, too, there are important gender differences between men and women. Men are more likely to be self-

employed than women. However, when we consider only those in non-tax registered enterprises, rates of self-employment

for males and females are identical at just over ten percent.

Almost one-third of self-employed men hire other workers, compared to fewer than one in six self-employed women

suggesting that enterprises owned by women are more likely to be survivalist in nature, with low returns. Female employers

also tend to employ fewer people than their male counterparts. The employees that females employ are also more likely to be

unpaid than the employees of male employers.

Three occupational categories accounted for the majority of self-employed women in 2016: elementary occupations, service

and sales workers and managers. This suggests a lack of occupational diversity within the sector and a bias towards less-

skilled occupations, particularly when the diversity of occupations within the managerial category is acknowledged. There is

also concentration in the industry of employment with just over half of self-employed women employed within wholesale

and retail trade, while a further fifth fall within CSP services. Only two other industries—finance and business services and

manufacturing account for more than ten percent of self-employed women.

Amongst females, Whites and Africans have the highest rates of self-employment. The self-employment gender gap is

particularly pronounced amongst Asians and Whites.

Non-tax registered self-employment rates are highest amongst Africans, with African women marginally more likely to be self-

employed than African men. As a result, Africans account for almost 90 percent of self-employed women in non-tax registered

businesses.

The largest cohort of self-employed women has incomplete secondary education. The bias towards lower levels of educational

attainment is even clearer when we consider the sample of non-tax registered self-employed women only. More than seven

out of ten of these women have not completed matric.

Access to business grants of any type are extremely rare for the informally self-employed, with less than one percent of

the self-employed reporting accessing a grant as their main source of funding – suggesting a limited reach of government

programmes and funding within the informal sector of the economy. Around two-fifths of the informally self-employed

reported not needing money to start their businesses. Close to half of those who did need money to start their businesses

reported using their own money, with just over one-tenth obtaining a loan. There were no discernible differences between

men and women in this regard.

Men were more likely to indicate that wage employment was the primary source of the money they used to start their

business. For women, the most commonly cited source of money used was from savings.

viiA GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)


Unemployment

Unemployment rates are higher for women than for men – however, the pattern across covariates is the same for both men

and women. Unemployment rates are highest amongst African and Coloureds, and lowest amongst Asians and Whites; they

are highest amongst the youth and lowest amongst the oldest working-age cohorts; they are highest amongst those with

lower levels of education, and lowest amongst those with tertiary qualifications; and they are lower in urban than in rural areas.

Taken together, all of these findings related to the labour market suggest that incentives to increase participation in the

economy cannot be gender-neutral. Further, the differences noted between women suggests that there should be a specific

targeting of women who are most vulnerable rather than just all women in general.

Constraints to SMME Growth and Entrepreneurship in South Africa

Access to credit and access to affordable credit are amongst the most regularly reported obstacles for growth amongst SMME

owners. Women face specific constraints in this regard. These include constraints due to traditional norms which exclude

women from accumulating assets and property, employment and income limitations, exclusions from financial and economic

decision making and adverse attitudes towards women. The lack of financial literacy of women compared to that of men is

also a major barrier that prevents women from being able to access credit in South Africa.

A 2014 study found that South African women score significantly lower than men in areas of financial control, financial

planning, choosing financial products, and general knowledge and understanding of finance (Roberts, Struwig and Gordon

2014). This may be because of a lack of female role models with financial literacy. This means that women may be unable to

improve their economic situation if they are unaware of the financial products which are available to them (Roberts, Struwig

and Gordon 2014). Therefore, it is vital to improve financial literacy for women in order to empower them to use financial

products for the promotion of entrepreneurship and other economic activities.

This is summarised in a quote from a study by the International Finance Corporation, which highlights “the need for a more

deliberate and integrated strategy focusing on women in business. Since women are the largest group of entrepreneurs in the

country, gender-focused business strategies must inform all BEE and financial access measures. Institutions which act now to

better understand and service this large, growing segment of South Africa’s business population will reap the benefit in the

future” (World Bank, 2006).

Overall, it is clear that when assessing the constraints to small business growth and entrepreneurship in South Africa, it is

important to take into account the extent to which these constraints disproportionately affect women. For example, while

policies enhancing access to credit are important for both the creation and growth of SMMEs, these interventions will

disproportionately support men if the gender-specific constraints to accessing finance for women are not also addressed.

Incentive Programmes as a Policy Instrument

The international review sheds some light on the ways in which the IDAD incentive schemes can best support entrepreneurs.

First, it is important to match potential beneficiaries correctly to the incentive that would best meet their own business

needs. Second, where funds are awarded, it is important to ensure that the values granted and the length of the support are

commensurate with the business’s needs, as well as the broader growth objectives envisioned by the programme. This is key

to the overall sustainability of both the financing institution and the recipient firm. Third, efforts should be made to ensure that

marginalised groups are able to access initiatives intended for their empowerment. This may mean supporting the facilitation

of the process of enterprise formalisation, where appropriate.

Lastly, it is important to consider a set of incentives that are specifically designated for female entrepreneurs which will

attract and retain females, thus increasing overall participation and lowering poverty and inequality. This will enable national

viii A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)

policy agendas to have a greater impact on the individuals most in need of assistance. This necessitates a well-coordinated

policy strategy, with collaboration across different government departments, levels of government and relevant external

organisations. Such a coordinated approach is vital in the South African context, given the various interlinked challenges to

women’s full participation in the economy that fall within the mandates of a number of different ministries.

The DTI’s Development and Administration Division (IDAD) administers and manages a number of incentive schemes targeting

different enterprises, but not women in particular. IDAD provides financial assistance through grants, loans and tax allowances

to emerging or expanding enterprises to promote economic development. The schemes are grouped into five clusters as

follows:

i. Broadening Participation, consisting of three schemes: the Black Industrialist Scheme (BIS), the Technology and

Human Resources for Industry Programme (THRIP), and the Support Programme for Industrial Innovation (SPII).

ii. Competitiveness Investment, consisting of four schemes: the Manufacturing Competitiveness Enhancement

Programme (MCEP); the Export Marketing and Investment Assistance (EMIA); the Sector-Specific Assistance

Programme (SSAS); and the Capital Projects Feasibility Programme (CPFP).

iii. Manufacturing Investment, consisting of five schemes: the 12I Tax Allowance Incentive (12I); the Automotive

Incentive Scheme (AIS); the Manufacturing Investment Programme (MIP); the Aquaculture Development Incentive

Programme (ADEP); and the Incubation Support Programme (ISP).

iv. Services Investment, consisting of two schemes: Business Process Services (BPS); and Film and Television Production

(Film and TV).

v. Infrastructure Investment Support, consisting of three schemes: special economic zones (SEZs); the critical

infrastructure programme (CIP); and the cluster development programme (CDP).

Women may receive support under any of these schemes. None of these schemes, however, explicitly target women. Data

related to female beneficiaries in particular does not appear to be collected for any of the incentive schemes apart from

Business Process Services (BPS); the Export Marketing and Investment Assistance (EMIA) and the Sector-Specific Assistance

Programme (SSAS). For each of these, there is considerable support for women despite these schemes not targeting women

in particular.

During the 2016/17 financial year, three provinces – Gauteng, KwaZulu-Natal and the Western Cape – accounted for the lion’s

share of incentive approvals and approved value. These three provinces accounted for approximately nine out of ten (88.8

percent) approved projects. These provinces include the five largest of South Africa’s eight metropolitan municipalities, which

are home to large populations and generate a disproportionately large share of total economic output. It is thus concerning

that other provinces do not seem to be accessing the incentives in greater numbers as investment in these more developed

provinces rather than the rest of the country may serve to reinforce existing geographical patterns of inequality.

By average value, projects in Free State were relatively high value on average, while those in the Western Cape were of relatively

low value on average. The projected investment ratio, defined as the ratio between the total estimated value of the additional

investment leveraged through IDAD incentives and the total value of these incentives, was highest for the Northern Cape,

with each R1 of IDAD incentives linked to R6.80 in additional investment. The Northern Cape is followed by the Free State and

Limpopo (both at a ratio of 4.2:1). In contrast, the ratio in Mpumalanga is just 0.4:1, meaning that each R1 of IDAD incentives is

linked to additional investment of R0.40.

On the metric of projected incentive cost per new job, the Northern Cape once again ranks highly with a cost of R0.3 million

per projected new job. The only province where this cost is lower is the Western Cape (R0.2 million per projected new job),

while in Gauteng the cost is R0.5 million per projected new job. The two provinces with the highest cost per projected new

job are Limpopo (R2.4 million) and the Eastern Cape (R1.9 million).

ixA GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)


In addition to the dti incentive schemes, there are programmes which specifically target women to facilitate their participation

in the mainstream economy. These are the Bavumile Skills Development Programme, the Isivande Women’s Fund (IWF) and

the South African Women Entrepreneurs Network (SAWEN).

The Bavumile Skills Development Programme targets women who wants to pursue their own business by offering them

20 days of training on sewing, knitting, weaving and craft (DTI, 2011). The main objective of this programme is to advance

women’s skills and expertise in arts and craft in order to produce better products (DTI, 2011). The substantial expansion in

the budget between 2015/16 and 2016/17—effectively a quadrupling of the budget—was accompanied by a more than

doubling from 300 to 700 in the number of female entrepreneurs trained.

The Isivande Women’s Fund (IWF) aims to enhance socio-economic development in rural, peri-urban and township areas by

empowering South African women (especially black women) through financial assistance of between R30 000 and R2 million

and non-financial support (DTI, 2011; n.d). The fund is involved with enterprises that seeks finance for start-up, for expanding

existing enterprises, for franchising, for business rehabilition and for gap finance (DTI, n.d.). The IWF supports SMMEs with

women ownership of more than 50 percent of the ordinary share capital and more than 30 percent in management positions

(DBSD, 2015 emb).

The South African Women Entrepreneurs Network (SAWEN) is a Section 21 registered company under the dti, with the main

objective to facilitate access to business resources, information and opportunities for South African women enterpreneurs

(SAWEN, 2012). This programme targets women specifically, who engage in informal income generating activities and/or

operate an SMME, or women who aspire to open a business, particularly rural based women-owned SMMEs (SAWEN, 2012).

Data to Support the Gender Analysis of Incentive Programmes

It is important that high quality (that is, accessible, usable, reliable and relevant) data be collected to enable effective M&E of

government programmes. Lack of data, as well as poor quality data, often places limitations on the types of evaluations and

analysis which can be conducted in respect of government programmes. This often means that we are unable to properly

assess whether these programmes are achieving their stated objectives and whether they are having a positive effect on the

lives of the most vulnerable South Africans in particular.

The costs of poor quality data are both social and economic. Lack of data and poor quality data have the potential to affect

an organisation’s reputation, affect its performance and could lead to loss of funds or revenue. In the specific context of this

project, the unavailability of good quality data means that it is not possible to undertake the proposed quantitative gender

analysis of dti incentives without collecting primary data.

Finally, we emphasise here that is imperative for the optimal functioning and benefit to be derived from the M&E system that

all eventual M&E activities be taken into account and built into government programmes up front. This requires clear M&E

planning undertaken at the outset of programme so that data processes, mechanisms and content are explicitly informed

by the M&E that will eventually take place with respect to the programme. If this is done, M&E will be facilitated: data for

monitoring purposes (and for picking up issues early on) will be available throughout the programme’s lifespan; and the data

may assist in strengthening the case for funding when it comes to budgetary applications.

Importantly, the initially envisaged quantitative analysis in this report would have been very straightforward to compile if

this type of approach to M&E was taken. Further, as this type of approach to M&E and data becomes more widespread, there

are potential synergies across government departments in terms of analysis, as well as in terms of identifying ‘packages’ of

interventions (i.e. combinations of interventions from different departments) that together might yield significantly stronger

results than either intervention on its own. An example would be the DoW and the dti collaborating on interventions to

improve the participation of women in the economy.

x A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)

Case Study Analysis of the Sector-Specific Assistance Scheme (SSAS)

SSAS was established in 2009 to foster industry- or sector-wide development with the specific objective of growing new export

markets, stimulating job creation and to broaden the export base. SSAS funding is only available to emerging exporters who

receive compensation for all qualifying expenditure that relates to developing such firms. IDAD administers one of two types

of funding provided under SSAS. Focusing on this project funding that is channelled towards sponsoring specific marketing

and sector-wide development projects overseen by the export councils, industry associations and joint action groups, we

conducted a survey of twenty-one SSAS beneficiaries to consider how women benefit from a dti incentive scheme such as

SSAS.

The SSAS guidelines do not distinguish between the treatment of female and male applicants and each receive similar

assistance and face the same application process and type of support. Despite this, women generally constitute the majority

of those that receive support from the SSAS incentive scheme. Over the full 2013/14-2016/17 period, female-owned SMMEs

accounted for 55.3 percent of all SSAS approvals.

Project coordinators as an important component of the administration of SSAS support

Firms wishing to participate in the SSAS incentive scheme must apply for support through a project coordinator who acts as

an intermediary between the dti and the applying firm. Project coordinators are uniquely placed in that they are aware of the

dti’s requirements and the SMMEs’ abilities and can navigate both parties’ needs. The dti officials responsible for overseeing

SSAS applications indicated to us that, in the 2017/18 financial year, they received applications from approximately 1 500 firms.

Project coordinators therefore play an integral role from a logistics angle as they review and finalise each of these applications

ensuring they meet the application standards and deadline. Feedback on rejected applications is also provided directly to the

project coordinators who then share it with each of the applicant firms and work with them to amend their application for

consideration in later rounds.

Project coordinators that are eligible to provide assistance to SMMEs include: Export Councils established through application

to the dti, Industry Associations, Provincial Investment and Economic Development Agencies; Business Chambers; the Small

Enterprise Development Agency (SEDA); Local municipalities; and Metropolitan councils. Based on data provided by the dti,

in the 2017/18 financial year, there were 26 project coordinators that represented 611 entities applying for the SSAS funding.

The shares of approved projects per type of project coordinator are presented in Figure 22. In the period under review, nearly

half of the SSAS projects approved were applied for through industry associations (45.3 percent), while a quarter of successful

firms applied through SEDA (24.4 percent). Of the remainder, similar proportions applied either through the export council or

provincial investment and economic development agencies.

Women in the SSAS-eligible sectors

The choice of sectors that qualify for SSAS support is informed by the IPAP, the dti’s premier industrialisation and economic

development policy document. These sectors are not fixed but can change based on the structural changes to the economy

and their resultant inclusion or exclusion in the IPAP. However, there is no consideration of gender as a criterion for which

sectors qualify for SSAS support.

The sectors that are currently priority industries for SSAS support are detailed in the dti’s SSAS Programme Guidelines (2013) as

follows: Agro-processing; Automotive; Business process outsourcing services; Capital equipment and allied services; Chemical

and allied industries; Civil engineering services; Consulting engineers; Creative industries; Electro-technical; Film production;

Metals and allied industries; Pre-qualified ICT services; and Textile and clothing.

Women account for a widely-varying share of employment within each of the twelve SSAS focus sectors for which data is

available in 2016. In virtually all subsectors, women are in the minority. Women account for the smallest shares of employment

xiA GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)


in the metals, civil engineering, and automotive subsectors. The only subsector where women are in the majority is the textiles,

clothing and leather subsector.

Gender gaps by race across the different SSAS-eligible sectors show that there are four sectors where the gender gaps in

employment are particularly large and may need tailored sector-specific attention. These sectors are the automotive, civil

engineering, metals and capital equipment sectors. The gender gaps in employment across sectors differ based on race, with

the African, Coloured and Asian race groups showing particularly high male-to-female employment ratios.

Measures of success

The dti measures success according to various metrics. One measure is whether the firm share of exports as a proportion of

turnover has increased since application. Second, they consider the number of export leads that the firm was able to convert

into direct sales following the export mission. Third, whether the firm has created employment following the export mission(s)

is considered. Fourth, financial growth is an important marker, specifically whether overall turnover has grown post-SSAS

support. Fifth, some of the firms that are supported did not have marketing or advertising material prior to receiving support;

after the export mission, they often have samples, marketing brochures and experience with setting up stands at these trade

shows. Post-support they have gained this vital experience as well as the actual samples that they can use in further domestic

and international marketing activities. Gender is however not considered in any of these metrics.

Survey results: Applications

The SSAS application process does not distinguish between male and female applicants, but this does not seem to be a

problem procedurally, as the process was categorised as being easy by both male and female respondents. Some concerns

were however raised by a minority of respondents.

Approximately half of respondents indicated that they had heard of the SSAS from either an investment or development

agency such as SEDA and Wesgro or from industry associations. In those few instances where firms heard of the support from

the dti directly, the respondents indicate that they were referred to other project coordinators to assist with the application

process.

The application process was categorised as being easy and straightforward due to the fact they worked with experienced and

knowledgeable project coordinators. Despite overall positive sentiment, two specific challenges were raised regarding making

the application. Firstly, it was noted that the dti often provided feedback at the last minute which made it difficult for firms to

plan accordingly. Secondly, respondent firms indicated that it was quite onerous to collect and compile the accompanying

documentation.

One drawback of using project coordinators to facilitate the application process may be the potential for gatekeeping (or the

perception of gatekeeping). This was alluded to by one respondent, who suggested that coordinators might choose not to

assist firms in the application process or share information on upcoming opportunities if they did not “like you or your firm”.

There is no evidence, though, that this is actually happening; nevertheless, such potential issues should be explicitly taken into

account when designing application systems and processes.

Male and female respondents identified similar reasons for applying for the emerging exports support, namely to grow their

export markets, to identify distribution partners and channels, and to undertake market research. In addition, female owners

identified three additional reasons. These were to seek out new marketing or display techniques from interactions at the

international trade shows; for brand exposure; and to compare the quality of products produced locally to those produced

internationally. This reveals that there may be some intrinsic differences between these categories of owners with regards to

their operating environment that might require different support.

xii A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)

Survey Results: Support Received

The support received from the dti was indicated to be sufficient by seventeen of the twenty-one respondents. Of the four who

indicated that the support was not sufficient, three female respondents indicated that markets are different across the world

and that the scheme is not designed to let them tap into their target market or assist with the distribution of goods across the

world or locally. One respondent felt that he had to do “everything himself”. These concerns may indicate a mismatch between

expectations and what the SSAS is designed to do, but also provide feedback that may be used to improve the experience of

beneficiaries.

In response to whether firms would require further dti support, four respondents (three females and one male) indicated that

they would like assistance with market research or marketing tools. Another female respondent indicated that she would like

assistance with understanding tax, excise duties and customs better. Six respondents, four of whom were male, indicated that

they would like assistance to procure machinery (capital) to stimulate production for both local and international markets, and

skills training for their staff. This suggests that a large proportion of the men interviewed view capital as a constraint to their

business and as a barrier to growing export production.

Eight respondents stated that they received no support from the project coordinator. Of these, half were female. It is unclear

as to whether these respondents requested support and did not receive it, or if support was simply unavailable to them.

Six respondents indicated that they received active support. This took the form of guidance on how to improve local sales

and how to use foreign contact to improve their business, the importance of marketing tools such as catalogues, and key

requirements for trade shows. This was in addition to courses run on various aspects of small business development.

The input from respondents on the ways in which project coordinators could improve the support provided varies across the

four sectors but relates to three common themes: preparation for the export show with a focus on networking and marketing,

capacity building workshops that touch on various aspects of business development and management, and more financial

support. This latter support however is out of the scope of what can be provided by the project coordinator.

Barriers to success for women-owned businesses

Across the different subsectors of the respondents, there were varying perceptions of the barriers that exist to female

entrepreneurs in establishing successful businesses. The range of challenges faced by women suggest that while the type of

support provided by incentives such as SSAS is sufficient in that, it fully covers the cost of participating in international trade

missions, as an incentive that seeks to foster industry- or sector-wide development the quality of support offered is lacking

because it fails to fully address the issues faced by businesses within the sector that will limit their ability to grow export

production.

In the metals subsector, most respondents were female and working as jewellery designers and producer. Respondents

indicated that access to markets and finance posed a key challenge. More specifically, knowledge relating to basic business

administration seems to be a challenge for female respondents, particularly around providing quotes and invoicing. With

regards to finances, the respondents cited the high start-up costs associated with setting up jewellery production as limiting

entry into the sector.

In agro-processing the challenges for female entrepreneurs seem more prominent. The industry is male-dominated and,

according to the five female respondents interviewed, it is very difficult for female entrepreneurs to access funding. There

also seems to be an unwillingness or reluctance from men in the industry to engage with female entrepreneurs, making it

challenging for women to partner with men to finalise deals

xiiiA GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)


The textiles, clothing and leather subsector is female-dominated, although our sample included an equal number of male

and female respondents. Respondents highlighted a lack of marketing skills as a challenge. Female respondents also note that

they are not taken as seriously as men in business related matters with the result that they often work harder to be considered

credible.

In the chemicals industries there were five respondents, four of whom were female. According to a female respondent, the

barriers faced by women seem to be no different from the barriers faced by men and include a lack of funding and difficulty

in penetrating markets. The male respondent indicated that there is also a lack of information about the sector available to

women and, in his opinion, a lack of support for women. Further, a female respondent noted that with the market being

extremely competitive it is difficult to gain credibility as a new entrant into the market. In this subsector there also seems to

be high operating costs which act as a barrier to women who struggle to access funding; this was also reported by a female

respondent.

Similar support is suggested by both male and female respondents to encourage greater female participation. This included

promoting greater awareness of dti incentives, organising workshops for small business owners on various topics, encouraging

greater access to funding as well as mentorship and business coaching.

Impact of SSAS

Firm turnover might have been affected in two possible ways by SSAS: first, through the direct channel of export markets

accessed through the export shows, and second through the improved product and business processes as well as contacts

made because of the export shows.

In our attempt to measure the impact of the SSAS support on the businesses’ export performance, we found that only five of

the 21 respondents reported an increase in their export sales as a proportion of total turnover, four of whom were female. As

to whether this improved export performance directly arose from SSAS support, eleven respondents (including five female

respondents) indicated that they had obtained at least one sale out of the export mission they attended. However, we cannot

say with certainty that the SSAS support was the main reason for the improved export outcomes observed, as many factors

may have contributed to the results observed.

In addition to this, the fact that more than half of respondents reported export sales as a direct result of the show but only

around one-fifth reported better export performance in the most recent year in comparison to when they applied suggests

that, even if the incentive is having a direct effect on exports achieved through the show, this is not being translated into

longer term improved export performance.

Regarding the indirect channel, export outcomes for the sample of firms suggest that an export marketing plan may be

important for achieving greater exports through the incentive. Other marketing materials such as brochures and samples that

can be improved through the incentive may also possibly be an avenue through which the incentive can lead to export sales.

However, evidence for this was limited.

Of the fifteen respondents who said that the event increased their knowledge of their buyers’ context, ten managed to make

export sales through the show. In terms of exports in the most recent year, however, only four reported a higher proportion of

total sales being exports than before the application was made, suggesting that other barriers to becoming exporters exist or

that the link between understanding the buyers’ market and exporting to that market is not very strong.

With respect to turnover, all but one of the firms saw increased turnover after receiving the SSAS support. It is however unlikely

that SSAS is the driving force behind this as the incentive focuses on increasing exports primarily and the evidence regarding

this specific outcome, as noted above, has not been strong for the sample.

xiv A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)

Regarding the overall impact of the incentive on financial performance and profitability, one in three respondents reported

that their business was not currently profitable. This remained unchanged from the situation prior to making the SSAS

application. Of the fourteen who reported that their business was currently profitable, nine said that they were also profitable

before they made the application. Thus, only five firms saw a positive shift in their profitability from the pre-SSAS period to the

post-SSAS period. Four of the respondents who indicated that their business was now profitable also indicated that it was not

profitable prior to the application.

Regarding plans for expansion, sixteen of 21 respondents indicated that they currently have plans for expansion. Nine of these

indicated that the support they received contributed to this decision in some way. It should be noted that reasons given for

this were not always related to the expansion in exports that the incentive aims for. There were also other indirect impacts on

respondents related to experience gained and learning because of the export shows. Interestingly, one female respondent

who was not currently profitable said that she was currently planning expansion because of the shows anyway “because

being able to attend the shows made me realise how much harder I need to drive my business to make it profitable”. Another

female respondent in the textiles, clothing and leather subsector indicated that the “trade show opened up the possibilities

for me in terms of thinking what I could do”. Another said that her plans for expansion were related to the support received as

due to the experience and information received, she “became confident and learnt the standards and guidelines”.

Regarding the impact of the incentive on the employment of women, 11 firms reported an increase in the number of female

employees in the most recent period after attending an export show. While some of these also reported an increase in exports,

these employment changes cannot necessarily be tied to the SSAS support received.

Perceptions regarding how the incentive benefits women specifically were mixed. Only ten respondents provided a response

when asked if women had benefitted from the SSAS support received. An equal number of these felt that women benefited

from the support received as did those who felt they did not benefit.

We also asked whether women had benefited from the incentive either through increased procurement from women-owned

businesses or partnerships formed with other women following the SSAS support. Only four female-owned businesses

indicated that they had either worked with or procured from woman-owned business since the application. However, two of

these business owners stated that this was not because of the SSAS support received. Impact in terms of greater procurement

from women thus seems to be limited, suggesting a further channel through which women can be empowered through such

incentives that is not currently being used to its full potential.

We reiterate that we cannot necessarily attribute all (or indeed any) of the results observed in the most recent year to the SSAS

incentive as many different factors contribute to changes in variables such as exports and turnover. We are therefore unable

to isolate the effect of the incentive on turnover, especially where this was not explicitly tracked by the businesses. This re-

emphasises that, for assessment purposes, the relevant data should be collected from beneficiaries throughout the process

so that robust conclusions can be reached about whether the programme is resulting in the intended outcomes and whether

these outcomes differ for different groups.

Recommendations

Ia. If government is serious about properly measuring and monitoring the performance and impact of incentive schemes,

the collection of relevant data must be prioritised.

Ib. Data collection for the purposes of measuring performance and impact of incentive schemes should be integrated into

the design of the scheme to ensure accuracy and completeness.

II. Women’s access to incentive programmes should be prioritised in order to effectively help address their historical and

continuing economic marginalisation.

xvA GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)


IIIa. To promote women’s fuller economic participation, incentive programmes and other types of support cannot ignore

those in the informal sector or those in rural areas or smaller urban centres.

IIIb. Where providing support to the informal sector is not feasible, for whatever reason, policy should focus on making

formalisation both an attractive option and a relatively straightforward process.

IV. The dti should monitor impact in terms of gender as a standard feature of evaluations of their interventions.

V. While assessments of incentive schemes and other similar interventions are economic in nature, it is worth trying

to understand their impact in terms that are not purely economic but which may in turn have important effects on

outcomes.

VI. The SSAS may need tailoring to account for the specific challenges faced by women and women-owned firms.

VII. South Africa should remain open to learning from the experiences of other countries and adapt policy where necessary.

1A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)


1. inTRoDUCTion

The centrality of the labour market to women’s ability to interact with the broader economy should not be understated. An


some of the various economic and social inequalities that exist between men and women. Importantly, allowing women

to take up productive employment helps ensure that society more broadly can directly reap some of the benefits of the

investment in women.

Globally women face significant challenges in the labour market and South Africa is no different. These challenges include

differentials in educational attainment and quality; interruption of labour force participation related to childbearing;

discrimination in terms of employment practices and wage determination; relatively fewer role models; vulnerability and weak

bargaining power; and environments that may be hostile to female membership of the workforce. Women typically also face

the consequences of gender norms and the unequal division of labour. This is due to women being seen as caregivers within

the family, while men are viewed as bread-winners.

Given these challenges, an outcome of various programmes undertaken by the Department of Women (DoW) is to ensure

the financial inclusion and support of women so that they can fully participate in the economy. Participation in the formal

sector holds the promise of higher incomes. Access to funding for women should not be underestimated due to its role

in securing the empowerment and advancement of women in the economy. In this regard, the DoW has identified the

incentives supervised by the Department of Trade and Industry (the dti) as the focus of this research. The objectives of the

dti are to encourage competitiveness and industrialisation of the economy, foster regional and international integration to

diversify markets for South African goods and services and to enable the increased participation of previously disadvantaged

members of the society in the formal economy.1

1 Source: http://www.thedti.gov.za/about_dti.jsp [Accessed: 20 August, 2018].

2 A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ADMINISTERED BY THE DEPARTMENT OF TRADE AND INDUSTRY (DTI)

The research need emanates from the DoW’s acknowledgment that women often struggle to access services, especially

those related to access to markets and funding, that the dti offers. Considering this, the DoW requested a gender analysis

of the services of the dti to determine whether women benefit from its services and funding and what the impacts of these

interventions are. This research aims to determine the extent to which women access and benefit from the services offered

by the dti. To do so, we conduct a quantitative analysis into the position of women within the South African economy as well

as an overview of the dti incentive programmes and the extent to which they currently benefit women. We also undertake a

qualitative case study into the Sector Specific Incentive Scheme (SSAS) and use this as a guide into how incentives should be

structured and implemented so that female participants can derive the maximum benefit from the given intervention.

Overall, this report aims to provide insights into three key questions related to how women have benefitted from and can best

benefit from incentives offered by the dti:


II. What impact do these incentives have on women, both directly (that is, through the impact on the beneficiary’s

business) as well as indirectly (that is, through the increased employment and procurement from other women

because of the incentive)?

III. Do the incentives adequately target and make provision for women within the process – from the application

process to the outcome? Ultimately this would indicate whether a gender-specific stream of the incentive is

necessary or whether a new incentive specifically targeted toward women would be more appropriate in the case

of the incentive under consideration?

Ultimately, it is hoped that the findings and policy recommendations of this research project will inform policy and interventions

that aim to ensure the integration of more women into the broader South African economy.

To this aim, section 2 of this report conceptualises women’s economic participation, highlighting the socioeconomic context

within which South African women find themselves. Section 3 provides a descriptive analysis of the dynamics of labour

force participation, employment and entrepreneurship. Section 4 provides a discussion of incentive programmes as a policy

instrument, including an international literature review and an overview of the dti’s incentive programmes in South Africa.

Section 5 provides an overview of the available data to support a gender analysis of incentive programmes, including a

discussion of the importance of data within a government’s monitoring and evaluation system. Section 6 provides a case study

on the Sector Specific Assistance Scheme (SSAS), including an overview of the programme and a discussion of the results of

a survey of SSAS beneficiaries. Section 7 highlights findings from the qualitative and quantitative analysis, and Section 8

provides policy recommendations and concludes.



2. Women’s eConomiC PaRTiCiPaTion

2.1 Conceptualising Women’s economic Participation

The centrality of the labour market to women’s ability to interact with the broader economy should not be understated. An


some of the various economic and social inequalities that exist between men and women. Families and governments

make substantial investments in children and young people and the existence of systematic barriers to women’s economic

participation represents an unnecessary, and costly, constraint on society’s ability to fully benefit from these investments.

For the purposes of this research, we consider women’s economic participation from the perspective of the labour market

only, and exclude aspects of participation related to their roles as consumers. Women’s participation in the labour market

encompasses a number of elements that begin with the decision to seek work and thus participate in the labour market

through to the financial and other outcomes associated with the employment they ultimately obtain. These processes,

broadly, can be classified as the following: (i) the decision to participate in the labour market; (ii) employment status in the

labour market; and (iii) the nature of employment (which in turn affects the ultimate financial result associated with the type

of participation in the labour market and economy).

Figure 1 presents these three processes as part of a broader consideration of economic participation through the lens of the

labour market. Various ultimate outcomes can be included as part of this conceptualisation: we list two, namely wellbeing at

both the individual and the household level, and inequality.

We begin with the decision to participate in the labour market. Here, the term ‘decision’ should not be conflated with the

idea of ‘choice’, since there are many instances where women do not have free choice on whether or not to participate. The

decision to participate is influenced by a variety of factors that operate at the individual, household or societal level. Some of

these factors are discussed in greater detail below, but may include the woman’s own preferences, her family circumstances,

or social norms around women working outside the home. The interplay of these and other factors together will determine

a country’s specific female labour force participation rate. Women who decide not to participate in the labour market—for

example, those engaged in tertiary education, those who remain at home, or those who are ill—are termed not economically

active.

Once counted among those in the labour force, an woman will either find employment or remain unemployed. Labour force

participants who are without work, but are willing and able to work and are actively seeking employment, are considered

to be unemployed according to the narrow definition of unemployment. Participants without employment who have not

taken active steps to find (or create their own) employment but who would work if offered employment, are defined as non-

searching unemployed (also referred to as discouraged workseekers). The broad definition of unemployment includes the

non-searching unemployed as part of the unemployed and, consequently, the labour force. Whether a woman finds work or is

unemployed (as well as whether or not she actively searches for work) is also affected by various individual and societal factors.

Together, these factors will determine the female unemployment rate.

Women who find work may be employed in various sectors and occupations; they may also be employed in either the formal

sector or the informal sector. They may be hired by another individual or a firm and thus be classified as an employee, or they

may choose (or be forced into) self-employment. If they are self-employed, they may be working alone or be an employer

themselves.

Irrespective of these modalities of employment, for all the employed, variation exists across employment outcomes.

These include remuneration, working conditions, protections and benefits, flexibility and so on. Again, the exact nature of

employment and the associated employment outcomes are affected by various individual and societal factors.


figure 1. Conceptualising economic participation through a labour market lens

Decide to

participate in the

labour market

Not

economically

active

Household

factors

Wellbeing (individual, household)

Inequality

Find

employment

Unemployed

Regional,

national

factors

Employed

Employment

outcomes

Self-employed or employee

Formal or informal sector

Industry

Occupation

Etc.

Yes

No No

Yes

Individual-level labour market outcomes—economic inactivity, unemployment or employment as mediated through

employment outcomes—play an important role in determining wellbeing at the individual and household level, as well as

influencing aspects such as income distribution at the societal level. At the same time, household, societal and macroeconomic

factors all influence the ultimate wellbeing outcome directly, as well as indirectly through their influences on decisions to

participate and the likelihood of finding employment. Indeed, wellbeing itself may influence the decision to participate.

Globally, women face significant challenges in the labour market and South Africa is no exception. These challenges are faced

with respect to all elements of their participation in the economy and include differentials in educational attainment and

quality; interruption of labour force participation related to childbearing; discrimination in terms of employment practices

and wage determination2; relatively fewer role models; vulnerability and weak bargaining power; and environments that

2 It is important to note here that women may be disadvantaged in the labour market not only by the type of employment that they are able to obtain, but also by discrimination against women in the labour market that affects the remuneration component of the third element of labour market participation only - that is, that even for the same work, women often receive a lower wage. Women can thus be disadvantaged at the following points in the labour market: the decision to participate, whether they become employed, the type of employment obtained and finally, the remuneration that they receive for their work. In this report, we do not focus on how women are remunerated in the labour market as this is beyond the scope of what an incentive offered by the dti would be able to achieve. Rather, dti incentives focus on how beneficiaries can be included in an economy that still excludes their participation in many ways. In this regard, where we refer to participation of women in the labour market and the economy, we are referring primarily to the decision to participate, obtaining employment and the nature of the employment obtained.



may be hostile to female membership of the workforce. Women typically also face the consequences of gender norms and

the unequal division of labour. This is due to women being seen as caregivers within the family, while men are viewed as

breadwinners.

Aside from income level and economic structure, the International Labour Office (2010) identify some of the most important

determinants of female labour force participation as: fertility; education; cultural and social norms, including religion;

institutions such as government policy, legal frameworks, and unions; political regimes; and the existence of violent conflict.

Below we briefly lay out how some of these factors have the potential to impact on the participation of women in the labour

market. We then proceed to consider how incentives such as those offered by the dti can be used to encourage and improve

women’s participation in the economy in light of the challenges faced by women in the labour market. We do not present this

as an exhaustive list of factors that influence women’s economic participation, but rather hope to provide a sense of some of

the wide range of issues that should be kept in mind.

fertility can play an important role in determining the ability and willingness of women to participate in the labour market.

Having children may impact directly on women’s ability to work during pregnancy and immediately after giving birth, and

indirectly in the longer term through responsibilities around care. In general, fertility and female labour force participation are

negatively related: where women have more children, they are generally more likely to exit the labour market, whether by

necessity or by choice. This relationship is also observed in South Africa: Ardington et al. (2015) find significant negative effects

of an additional child on female labour force participation.

education is central to gender equality as it both directly and indirectly impacts an individual’s ability to participate fully in the

economy. In South Africa, there has been substantial movement toward gender equality in education over the post-apartheid

period, with women now outnumbering men in enrollment in higher education. However, gender differentials remain in both

the level and type of education received. Women remain less likely than men to enrol in masters and doctoral degrees, despite

their greater share of higher education enrollments (DoW, 2015). There is also segregation regarding the subjects that women

are likely to study. Women are less likely to be enrolled in mathematical or science related fields; while women make up more

than half of all matriculants, they make up less than half of all matric passes in mathematics and science. This feeds into tertiary

education outcomes, where women are less likely to be enrolled in STEM fields (DoW, 2015).

Women’s education may impact on the decision to participate in the labour market through three distinct channels (Diwan

& Vartanova, 2017). First, education is linked to skills and, by extension, to remuneration. By raising the wages that women

might expect to earn, education increases the opportunity cost of not working, putting upward pressure on participation

rates. Second, education may weaken women’s own patriarchal values, eroding this as a barrier to working outside of the

home. Finally, education may strengthen women’s bargaining power within their households, facilitating their labour force

participation.

Internationally, higher levels of education—and tertiary education in particular—are linked to higher rates of female labour

force participation (ILO 2017). In developing countries, tertiary education raises the likelihood of women’s labour force

participation by 10.5 percentage points, while the effect in emerging economies is a 15.3 percentage point increase (ILO

2017). There is also a direct link between level of education and employment outcomes, in terms of both probability of finding

employment and wage outcomes once employed.

Ntuli and Wittenberg (2013) use decomposition analysis to explain the observed increase in labour force participation of

African women during 1995-2004. They show that African women are more likely to enter the labour force if they have higher

education and assume urban residency, but that labour force participation does not guarantee employment. Bhorat and

Leibbrandt (1999b) find that, for African women, personal, household, and regional variables are significant determinants of

labour force participation in South Africa.


social norms around gender roles arise from a variety of sources and can strongly influence both female labour force

participation and the types of jobs that women choose or are able to choose. Indeed, Diwan and Vartanova (2017) argue that

“culture seems to operate through societal mechanisms that override individual preferences”; the pace of cultural change then

determines the rate at which female participation rates are able to change.

Dao (2014) analyses determinants of female labour force participation with a specific focus on societal norms in developing

countries. In a sample of 21 countries, including South Africa, norms related to single parenthood, the role of the housewife,

whether men are superior political and business leaders, and notions of good working hours are all found to influence the

female labour force participation rate. Norms and beliefs around the role of women in the home play a key role, and are often

strongly influenced by religion. Besamusca et al. (2015) argue that “gender stereotypes encapsulated in religious practices

affect female labor force participation primarily through strong beliefs regarding the role of mothers”. In their analysis of 117

countries, they find the strongest effect of religion for women aged 20-59 years.

In South Africa, there is evidence of gender-based discrimination in the labour market. Not only are women less likely to be

employed than men (Oosthuizen, 2006; Leibbrandt et al, 2010), but they also earn lower wages than men with the same

endowments (Burger and Yu 2007; Casale & Posel, 2010; Muller, 2009; Ntuli, 2007). This indicates that women face worse labour

outcomes than men at least partly because of societal norms which serve to discriminate against women in the workplace.

Within the context of the household, women’s bargaining power plays an important role in the extent to which they are able

to choose to participate in the labour market. Casale (2002) show that there has been increased feminisation of the labour

market in the post-apartheid period, and attribute at least some of this factors such as lower marriage and fertility rates and

changes in household structure. Critically, the distribution of intra-household bargaining power is also an outcome of women’s

ability to engage in the labour market—often linked to their relative financial contribution to the household—suggesting a

circular process that might be difficult to disrupt in particular contexts.

Another set of factors relates to the fact that care responsibilities within households are typically and overwhelmingly the

domain of women. This allocation and the extent to which care might be shared with men are strongly influenced by social

norms. Further, the degree to which care constraints women’s economic participation may vary according to the individual

woman’s age, education or marital status. Care responsibilities may reduce female participation in the economy by preventing

participation entirely, as well as by requiring a reduction of the intensity of participation. In other words, women may either be

forced out of the labour market entirely, or they might need to switch to part-time work.

Recent work on time allocations to market and home production across the lifecycle in South Africa suggest that women’s

care responsibilities displace time for market work. In 2010, women between the ages of 20 and 29 years are estimated to

have spent 2.3 hours per day in market production activities, and 4.7 hours in household production activities. While men

spend more time in market production than women, the opposite is true for household production. In both age groups,

women spend more time in total in productive activities than men: amongst 20-29 year olds the difference is 19 percent, while

amongst 30-49 year olds it is eight percent.

Table 1. mean time spent in market and home production by gender in south africa (hours per day)

activity 20-29 years 30-49 yearsmale female f:m ratio male female f:m ratio

Market 3.9 2.3 0.58 5.8 3.5 0.61

Household 1.9 4.7 2.44 1.6 4.4 2.82

Care 0.1 0.8 6.64 0.2 0.6 3.62

Housework 1.8 3.8 2.14 1.4 3.8 2.73

Total 5.8 6.9 1.19 7.4 8.0 1.08Source: Own calculations, Oosthuizen (2018).

Notes: Figures calculated as unweighted averages of per capita values for each single-year age cohort in each age group.



Based on data for 2000 for South Africa, Floro and Komatsu (2011) find that “while women’s and men’s hours of unpaid work

do not vary greatly across employment status, these obligations affect women’s employment options and their ability to look

for work”. The often-cited policy imperative of increasing women’s economic participation does not always recognise that,

on average, women are already spending at least as much time as men in productive activities and increasing time spent in

market work is often not accompanied by reallocations of their care work to other household members and men in particular.

It is in this context that institutions, such as maternity leave and availability of childcare, may play an important role in

supporting women’s economic participation. Besamusca et al. (2015) find the relationship between length of maternity leave

and female participation rates to have an inverted U-shape: particularly short and particularly long leave entitlements in their

sample of 117 countries are found to be associated with reduced participation.

2.2 The Role of the dti in Promoting Women’s economic Participation

Given the challenges faced by women in the economy, an outcome of various programmes undertaken by the Department

of Women (DoW) is to ensure the financial inclusion and support of women so that they can fully participate in the economy.

Participation in the formal sector holds the promise of higher incomes. Access to funding for women should not be

underestimated in its role in the empowerment and advancement of women in the economy.

While the dti cannot directly affect such factors as fertility, cultural norms and household influences that have an effect on the

participation of women in the economy, it can provide incentive funding to assist women to improve their financial positions

and through doing this create an enabling environment for women’s participation in the economy by taking the specific

challenges that women face into consideration in designing incentives and by targeting women in particular.

In this report, we focus specifically on how the dti incentives can influence participation in the economy and improve the

inclusion of women in the economy through its incentives that focus on expanding South African businesses.

In terms of participation, in line with the outline of labour market participation above, the dti can have an impact on either of

the components of women’s participation in the economy listed above through the incentives it offers:

i. It can influence the decision to participate in the labour market by empowering women in a manner that changes

cultural norms that may be limiting participation currently: a more representative economy will go some way

towards changing norms that currently restrict women’s participation in the economy.

ii. It can increase the likelihood of finding employment for women through investing in programmes that encourage

growth of businesses owned by women and employment of women through the support of such business growth.

iii. It can contribute toward the types of employment and, specifically, self-employment opportunities available to

women.

Because dti incentives are aimed at assisting businesses to grow, they will have a direct effect on women’s participation in the

labour market in respect of self-employment primarily through the support of women-owned businesses. We will thus focus

on this aspect of how dti incentives can impact on women’s participation in the economy in this report.

Importantly, we recognise however that through supporting the growth of women-owned businesses (and small businesses

more generally), the dti incentives can also also have a secondary effect on the economic prospects for women as growing

businesses employ more workers, procure from other companies and contribute increasing tax revenues, all of which also have

the potential to affect women positively. We also note that the greater representation of women in the economy achieved

through such incentives can have a broader cultural effect that serves to increase women’s participation in the economy as

well.


Within the context outlined above, in this report, we concern ourselves with three key questions in this report related to the

dti incentives and women in South Africa:


II. What impact do these incentives have on women?

III. Do the incentives adequately target and make provision for women - from awareness to the application process

to the results of the incentive? Ultimately, this would indicate whether a gender-specific stream of incentives or

separate incentives targeted at women are necessary.

To provide insights to the first of these questions, we consider the administrative data available regarding the dti incentives.

We also consider one particular incentive (SSAS) as a case study that might provide some useful insights in this regard.

Regarding impact, we consider whether the data required to make this assessment is available. We consider the available data

and make recommendations as to how best to collect the data required for this purpose in the future. We also consider the

impact of one particular dti incentive (SSAS) on women through a survey of SSAS beneficiaries.

Regarding the third question, first we consider where women are currently employed in the South African economy and

where they are currently participating in the economy with the aim of seeing where dti incentives should be focused to have

an effect on women where it is most needed. We focus on self-employment as this is where dti incentives can most effectively

be targeted but also note overall employment and labour force participation rates as being suggestive of sectors and areas

where incentives should be targeted as knock-on effects of dti incentives can serve to empower women in those spaces

where such empowerment is most needed.

We then also consider how incentives can be better designed to accommodate women and the challenges they face

specifically. We do this through a consideration of one dti incentive (SSAS). We also consider whether any lessons can be learnt

from what is being done in a number of other countries.



3. Women’s eConomiC PaRTiCiPaTion in soUTH afRiCa

3.1 The labour market Context

3.1.1. overview of the labour market

Table 2 provides a high-level overview of the South African labour market using two data sources. The most recent estimates

are for the second quarter of 2018 and are derived from the QLFS data for that quarter. We also provide estimates from the

2016 LMD data, since this is the dataset that we will be relying on for later more detailed analyses.3

In 2018Q2, the working-age population is estimated at 37.8 million in total, with women slightly outnumbering men and

accounting for 50.5 percent of the total. The employed numbered 16.3 million, while a further 6.1 million were unemployed

according to the narrow definition of unemployment. Almost 2.9 million individuals were classified as being non-searching

unemployed. As a result, expanded unemployment stood at 8.9 million, while the expanded labour force was 25.2 million

(compared with 22.4 million for the narrow labour force).

Table 2. labour market statistics by gender, 2016 and 2018Q2

2016 2018Q2male female Total male female Total

aggregates (‘000s)Working-age population 18 102 18 567 36 669 18 710 19 122 37 832

Employed 8 906 6 874 15 780 9 154 7 134 16 288

Narrow unemployed 2 926 2 827 5 753 3 097 2 986 6 083

Narrow labour force 11 832 9 701 21 533 12 251 10 119 22 370

Expanded unemployed 3 995 4 143 8 138 4 367 4 579 8 947

Expanded labour force 12 901 11 018 23 919 13 521 11 713 25 234

Non-searching unemployed 1 069 1 316 2 386 1 270 1 594 2 864

Rates (%)Employment-to-population ratio 49.3 37.2 43.2 48.9 37.3 43.1

Narrow unemployment rate 24.7 29.1 26.7 25.3 29.5 27.2

Expanded unemployment rate 31.0 37.6 34.0 32.3 39.1 35.5

Source: StatsSA, Labour Market Dynamics (2016); Quarterly Labour Force Survey (2018Q2).

There are important gender differences in some of these aggregates, however. For example, men outnumber women amongs

the employed by more than two million; in contrast, the gap is just over 100 000 within the narrow unemployed, while there

are around one-quarter more women than men amongst the non-searching unemployed. As a result, women account for

just over 51 percent of the expanded unemployed. In other words, men form the majority of those with better labour market

outcomes (employment as opposed to unemployment) and women dominate amongst those with worse labour market

outcomes (non-searching unemployment as opposed to narrow unemployment).

The implication of these differences is that working-age women are less likely than their male counterparts to be employed,

and that economically active women are more likely than men to be unemployed. For example, the national employment-to-

population ratio in 2018Q2 was 43.1 percent, but there was a difference of 11.6 percentage points between the ratios for men

and women. Thus, nearly half of all working-age men were employed, compared to 37.3 percent of working-age women. At

3 Our preference for the LMD data over the QLFS data for later analyses is related to sample size: the LMD data has approximately four times the sample size available in the QLFS. This larger sample size means that the more detailed disaggregations presented below are more credible than would be the case if a single QLFS dataset were to be used.


the same time, female unemployment rates are higher than those of males: the difference was 4.2 percentage points for the

narrow unemployment rate, and 6.8 percentage points for the expanded unemployment rate. Similar patterns are observed

for the 2016 estimates.

box i. selected labour market Definitions

Working-age population: All individuals in the population between ages 15 and 64, irrespective of economic activity.

labour force: All individuals of working age who are either employed or unemployed (i.e. the labour force consists of all

who are willing and able to work).

employed: All working-age individuals who worked for at least one hour during the reference week. Individuals who were

temporarily absent from a job or their own business during the reference week are also considered employed.

Unemployed (narrow): Working-age individuals who, during the reference week, were not employed, but who were

available to work and actively sought employment (a job, or starting their own business) in the four weeks prior to the

survey. If the individual had not actively sought employment, but had a job or business to start at a definite date in the

future and were available, then they are also classified as unemployed.

non-searching unemployed: An individual of working age who was not employed during the reference week, who

wanted to and was available to work, but took no active steps to find employment or start their own business. The main

reason for not seeking work should be either a lack of available jobs in the area; an inability to find work utilising his/her

skills; or the loss of hope of finding any form of work. These individuals are also referred to as the non-seeking unemployed.

expanded unemployment: All individuals who are unemployed (as per the narrow definition), as well as all discouraged

workseekers.

labour force participation rate: The proportion of the working-age population who are members of the labour force (i.e.

who are either employed or unemployed).

Unemployment rate: The proportion of the labour force that is unemployed.

informal sector: The informal sector comprises: (1) employees working in establishments that employ fewer than five

employees and who do not deduct income tax from their wages; and (2) employers, own account workers and individuals

helping unpaid in household businesses that are not registered for either income tax or value-added tax.

formal sector: The formal sector includes all employment not included in the informal sector, but excludes domestic

workers.

Source: Statistics South Africa (2014).

3.1.2 labour force Participation

Working-age adults all decide whether or not to participate in the labour market. This decision is affected by numerous factors

at the individual, household and societal levels, and as a result may not necessarily be an accurate reflection of an individual’s

preference. Different groups may experience differing pull and push factors or may face unique constraints on their decisions;

as a result, there may be systematic differences in the likelihood with which different groups participate in the labour force.

This likelihood of participation is reflected by the labour force participation rate, the share of the working-age population

that is economically active (i.e. either employed or unemployed). Figure 2 presents gender-specific labour force participation

rates for South Africa since 2016. Labour force participation rates amongst women are substantially lower than those of men,



irrespective of the unemployment definition used. In the fourth quarter of 2018, the narrow labour force participation rate

amongst males (65.5 percent) was 12.6 percentage points higher than that of females (52.9 percent). Using the expanded

definition, the gap was 10.3 percentage points even though the level of participation for both males and females is higher.

figure 2. labour force participation rates by gender, 2016-201865

.252

.464

.551

.466

.052

.365

.752

.966

.654

.666

.353

.666

.453

.765

.252

.565

.653

.265

.552

.9

73.2

61.9

72.5

61.1

73.3

62.1

72.8

62.6

73.9

63.8

73.5

63.1

73.7

63.5

73.0

62.5

73.6

63.8

73.7

63.4

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

2016

Q1

2016

Q2

2016

Q3

2016

Q4

2017

Q1

2017

Q2

2017

Q3

2017

Q4

2018

Q1

2018

Q2

2016

Q1

2016

Q2

2016

Q3

2016

Q4

2017

Q1

2017

Q2

2017

Q3

2017

Q4

2018

Q1

2018

Q2

Narrow Definition Expanded Definition

MaleFemale

Gender

Perce

nt

Source: StatsSA, Quarterly Labour Force Survey (various years).

While men are more likely than women to participate in the labour force, in the years following the democratisation of South

Africa, female labour force participation increased dramatically (Casale and Posel, 2002). While this is a good signal pointing

to the integration of women into the economically active population, Casale (2004) observes that this increase translated

into an increase in unemployment rates for the country. At the time, she found that there had been some opportunity for

advancement of females in the labour force, but that white women seemed to have been the main beneficiaries.

Labour force participation rates in South Africa are low by international standards as illustrated in Figure 3. Of eight other

developing countries from around the world and the Sub-Saharan Africa region as a whole, South Africa’s male labour force

participation rate is the second-lowest (62.0 percent), and the female labour force participation rate—at 52.2 percent—is

lower than in all the listed countries, except Mexico and Nigeria. The participation rate for women in South Africa is 12.1

percentage points lower than for the entire Sub-Saharan African region, and this gap is even wider when considering the

participation rates for the population aged 15 years and older (as opposed to 15 to 64 year olds). Two immediate factors

contribute to this low level of labour force participation: first, the relatively small size of the informal sector in South Africa and,

second, the constrained smallholder and subsistence agriculture sector as a source of employment in South Africa.


figure 3. labour force participation by gender, various countries, 2017

80.4

59.5

79.3

57.5

82.8

68.8

86.4

63.8

80.076.3

82.5

47.3

80.6

54.759.9

50.3

74.6

64.3 65.2

52.2

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0Pe

rcent

BrazilChile

China

ColombiaGhana

Mexico

MalaysiaNigeria

Sub-Saharan Africa

South Africa

MaleFemale

Gender

Source: World Bank (2018).

Notes: Estimates are ILO modelled estimates for the population aged 15-64 years.

Table 3 elaborates on the gender difference in participation rates, disaggregating by location and race. Irrespective of the

disaggregation, males have the highest labour force participation rates. Amongst Africans and Coloureds, male labour force

participation rates are roughly 12 percentage points higher than those of women. This gap is, though, substantially wider

amongst Whites (19.5 percentage points) and Asians (29.7 percentage points). Male participation rates range between 63.2

percent (African men) and 77.3 percent (White men). This contrasts with the participation rates for women, which range

from 45.5 percent amongst Asian women to 58.3 percent amongst Coloured women. Thus, the highest female labour force

participation rate (that of Coloured females) is lower than the lowest male participation rate (that of African males).

Table 3. labour force participation rates by gender and location, 2018

Urban Rural overall

male female Total male female Total male female Total

African 72.4 61.7 67.1 48.3 37.4 42.7 63.2 52.1 57.6

Coloured 71.8 57.9 64.6 76.5 63.6 70.4 72.1 58.3 64.9

Asian 74.9 45.6 60.6 93.6 24.3 85.1 75.2 45.5 60.9

White 76.7 58.0 67.3 87.8 52.8 71.7 77.3 57.8 67.5

Total 72.9 60.2 66.5 49.4 38.0 43.5 65.5 52.9 59.1

Labour Force (‘000s) 9 326 7 739 17 065 2 925 2 380 5 305 12 251 10 119 22 370Source: StatsSA, Quarterly Labour Force Survey (2018Q2).

In urban areas, male labour force participation rates across race groups are very similar with almost three-quarters of men

participating in the labour force. Indeed, labour force participation rates for all four race groups are within five percentage

points of each other. Amongst urban females, the range of participation rates is three times wider: participation rates are

lowest amongst Asians (45.6 percent) and highest amongst Africans (61.7 percent). On average, 60.2 percent of urban women

are active in the labour force.



In rural areas, though, South Africans are much less likely to be economically active: just 43.5 percent of rural adults participate

in the labour force in 2018. Unlike in urban areas, there is wide variation across race groups in participation rates amongst

both males and females. Amongst males, participation ranges from around five out of ten (48.3 percent) amongst Africans to

around nine out of ten amongst Asians and Whites; amongst females, it ranges from fewer than three out of ten (24.3 percent)

amongst Asians to more than six out of ten (63.6 percent) amongst Coloureds. Thus, as is the case in urban areas, the range in

rural areas is much wider for females than males.

The above analysis highlights the low levels of economic participation of women (and men) in non-urban areas, a large part

of which is made up by the former homeland areas. These low levels of labour force participation have implications for the

extent of poverty in areas and this is where government programmes targeted at supporting businesses may face challenges

in reaching potential beneficiaries. One reason for this is that information that is readily available on government programmes

may not be easily accessible in non-urban areas. Another reason is that businesses themselves in non-urban areas may be

more marginal and may require different types of interventions compared to urban enterprises.

3.1.3. employment

3.1.3.1. Employment by industry

In section 3.1.1, women’s disadvantage in terms of likelihood of employment was highlighted. Gender differences, though,

extend beyond high-level labour market outcomes and are observable in various areas of employment.

Within employment, men and women are not necessarily similarly distributed across industries, as illustrated in Figure 4. The

figure plots the ten major industries in terms of the share of male employment they account for (the horizontal axis) and the

share of female employment they account for (the vertical axis). The dotted 45° line represents equality between the shares

of male and female employment. In other words, if an industry accounts for 10 percent of male employment and 10 percent

of female employment, it would be located on the dotted line. Industries located below the line account for relatively large

shares of male employment; those above the line account for relatively large shares of female employment. However, given

that men outnumber women within employment, the figure does not reveal which gender dominates employment within

a given industry. To answer this question, the ratio of male to female employment is provided in parentheses, with ratios less

than one indicating that women dominate employment.

Female employment is concentrated in four industries: community, social and personal (CSP) services (31.4 percent);

wholesale and retail trade (22.1 percent); private households (14.6 percent); and finance (13.2 percent). Together, these four

industries account for 81.3 percent of total female employment. In contrast, male employment is less concentrated with five

industries each accounting for between 13 percent and 19 percent of total male employment. The four industries accounting

for the largest proportions of total male employment—wholesale and retail trade (18.6 percent), CSP services (15.6 percent),

finance (14.6 percent), and construction (14.1 percent)—together account for 62.9 percent of male employment. This lower

concentration of male employment within a small number of industries is the reason why the right-hand side of the figure

lacks any industries.

Women dominate employment in only two industries: CSP services, which includes government, and private households,

which is primarily domestic work. In CSP services, the ratio of male-to-female employment is 0.6, indicating that for every ten

women employed in the industry, there are six men. Within private households, the gap is even larger, with only three men for

every ten women in the industry. In contrast, construction, mining and transport are heavily male dominated, with ratios of 8.0,

6.4 and 4.3. Thus, in construction, there are eight times as many men in the industry than there are women. In manufacturing,

agriculture and utilities, men outnumber women by a ratio of between 2.0 and 2.5 to one, while in wholesale and retail trade

(1.1) and finance (1.4) the ratios are much lower.


figure 4. Distribution of employment across industry by gender, 2016

Agriculture (2.3)

Mining (6.4)

Manufacturing (2.0)

Utilities (2.5)Construction (8.0)

W&R trade (1.1)

Transport (4.3)

Finance & business services (1.4)

CSP services (0.6)

Private households (0.3)

Relatively large share of male employment

Relatively large share of female employment

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0Sh

are of

Fema

le Em

ploym

ent (%

)

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0Share of Male Employment (%)

Source: StatsSA, Labour Market Dynamics (2016).

There are various reasons for these differences between industries. For instance, women have historically not been employed

in large numbers in industries where jobs are dangerous and require physical strength. Thus, relatively few women have been

employed in mining and construction. Such patterns may be perpetuated by attitudes towards women’s employment in

those sectors (held by both men and women), as well as attitudes, preferences or even discrimination on the part of firms.

Conversely, women’s dominance in CSP services is explained by the fact that female-dominated occupations such as nursing

and teaching are concentrated within the industry; similarly, the vast majority of domestic workers in South Africa are female,

explaining their dominance within private households. Globally, services sectors are found to be more accessible to women

(ILO, 2010), explaining the relatively narrow gap in wholesale and retail trade and finance and business services.

3.1.3.2. Skills distribution of employment

These ten industries also differ in terms of their skills intensity and, as a result, women of different skills levels are distributed

differently across industries (Table 4). Of the almost 6.9 million employed women in 2016, almost one-quarter (1.7 million)

are classified as high-skilled. Those in semi-skilled occupations account for 40 percent of employment, while the low-skilled

represent 35 percent of employment.

The majority of high-skilled women (57.0 percent) are employed in CSP services, while a further 21.1 percent are employed in

finance and business services. These two industries therefore account for almost four-fifths of the employment of high-skilled

women. In both instances, these shares are substantially larger than their shares of total female employment (31.6 percent and

13.8 percent). Although they are much smaller, utilities and transport account for relatively large shares of high-skilled female

employment compared with their shares of total female employment.



Table 4. Distribution of employed women across industry by skills category, 2016

industry High-skilled semi-skilled low-skilled TotalAgriculture 0.4 1.3 9.2 3.9

Mining 0.5 1.3 0.6 0.9

Manufacturing 6.1 11.9 5.5 8.2

Utilities 0.9 0.6 0.1 0.5

Construction 1.4 2.1 3.2 2.3

W&R trade 9.7 31.7 19.6 22.0

Transport 2.9 3.6 0.9 2.5

Finance & business services 21.1 15.5 6.9 13.8

CSP services 57.0 31.3 14.5 31.6

Private households 0.0 0.7 39.5 14.3

Total 100.0 100.0 100.0 100.0

Employment (‘000s) 1 686 2 750 2 439 6 874


Two industries—wholesale and retail trade, and CSP services—each account for just under one-third of semi-skilled female

employment. In the former, this is almost ten percentage points higher than the industry’s share of total female employment,

but in the latter the two proportions are similar. These are followed by finance and business services (15.5 percent) and

manufacturing (11.9 percent), both of which account for relatively large shares of semi-skilled female employment.

Employment of low-skilled women is concentrated in private households (39.5 percent), wholesale and retail trade (19.6

percent) and CSP services (14.5 percent), although of these three industries it is only private households that accounts for a

disproportionately large share of low-skilled female employment. Agriculture accounts for 9.2 percent of low-skilled female

employment, more than twice the industry’s share of total female employment (3.9 percent).

Table 4 provides a way of thinking about the structure of incentive schemes offered to women of different skills sets across

different sectors. For instance, the low proportion of high skilled women in agriculture, mining, electricity, construction,

transport and households implies that incentives designed for women in these industries should not have requirements that

are too onerous, and by design should be made accessible to the skills set of women where they are employed. An example

of this includes, perhaps, not making application processes too technical. Further, access to technology may be a challenge for

women with lower skills sets, and these factors should be considered in the incentive design and application process.

An integral and supplementary part of understanding the skills set of employed women relates to educational attainment.

Figure 5 presents the educational attainment of employed women, distinguishing also between youth (15 to 34 year olds) and

non-youth (35 to 64 year olds). A key motivation for doing this is the relatively rapid improvements observed in educational

attainment over the past few decades, which will have implications in terms of incentive design if programmes are to be

accessible to all women. Youth status is associated with differences in educational attainment amongst employed women.

Amongst employed female youth, 41.0 percent have completed secondary education, while a further 30.9 percent have

incomplete secondary education. Just 4.5 percent of these women do not have any secondary education at all, while just over

one-quarter have either a diploma/certificate or a degree.


figure 5. educational attainment of employed women by youth status, 2016

6.6

5.8

18.5

17.4

26.6

41.0

30.7

30.9

16.8

4.5

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0Percent

Degree

Diploma/Certificate

Complete Secondary

Incomplete Secondary

Primary only

Youth (15-34 years)Non-youth (35-64 years)

Age Group


Note: Proportions may not add to 100 due to the omission of the “Other/unspecified” category.

In contrast, amongst employed women aged 35 years and above, the largest cohort has incomplete secondary education

(30.7 percent), while 26.6 percent have a matric certificate. This latter proportion is 14.4 percentage points lower than that

of their counterparts under the age of 35 years. Older women are far more likely to have no secondary education at all: 16.8

percent of employed women aged 35 years and above have only (some) primary education, more than three times the

proportion of their younger counterparts. Interestingly, despite their age advantage, the proportion of employed women with

post-secondary education is only marginally higher for non-youth than for youth (25.1 percent compared to 23.2 percent).

Differences in educational attainment may have significant implications in the ability of employed women to access

government programmes, including those offered by the dti. Lower levels of education may mean that complex or detailed

application forms, as well as online application systems, may represent more significant barriers to entry for these women,

thereby preventing access even before the merits of their particular situation can be evaluated.

3.1.3.3. Formality and informality

An important consideration for creating incentive programmes, and indeed ensuring that they are able to reach women, is to

understand the role of informality in supporting the livelihoods of women. Of all employment in South Africa, three-quarters

(74.6 percent) is located within the formal sector and just 17.3 percent falls within the informal sector. The remaining 8.1

percent is located within private households.

Males are more likely than females to be employed in the formal sector (77.1 percent compared to 71.4 percent), and in the

informal sector (19.5 percent compared to 14.4 percent). In contrast, private households account for 14.3 percent of female

employment, more than four times the share for males. As a result of these differences, women account for around two-fifths

(41.7 percent) of formal sector employment and just 36.2 percent of informal sector employment. In contrast, three out of four

(76.5 percent) workers in private households are women.



Table 5. employment by sector, 2016

formal sector informal sector Private Households Total

Total employed (‘000s) 11 772 2 725 1 283 15 780

Distribution (%)

Total 74.6 17.3 8.1 100.0

Male 77.1 19.5 3.4 100.0

Female 71.4 14.4 14.3 100.0

Female share of sector (%) 41.7 36.2 76.5 43.6

share of female employment (%)

African 68.2 86.2 91.2 74.1

Coloured 12.6 5.8 8.3 11.0

Asian 3.4 1.2 0.2 2.6

White 15.9 6.8 0.3 12.4


There are important variations by race in this general pattern. Africans constitute a relatively large proportion of female

employment in the informal sector (86.2 percent) and in private households (91.2 percent) compared with their share of total

female employment of just under three-quarters (74.1 percent). Conversely, Coloured, Asian and White women account for

relatively large proportions of formal sector employment.

These statistics show that when considering the implementation of incentive programmes, it is key to take into account

the fact that women are employed across these three sectors and that their needs and constraints may therefore differ

systematically. Out of 100 employed women, approximately 30 are employed outside of the formal sector and, of these,

between 25 and 28 are African and another one to two are Coloured. A narrow focus on the formal economy means that a

relatively large proportion of employed women are overlooked, the vast majority of whom are African or Coloured and who

are typically marginalised within the formal sector.

3.1.4. Women in self-employment

Self-employment represents an alternative to working as an employee for many working-age adults. However, it is important to

remember that self-employment spans a wide range of activities, ranging from individuals running SMMEs in the formal sector

to individuals engaged in survivalist activities in the informal sector. From the perspective of women’s economic participation

and the need for supportive policies, this is an important distinction given that the needs and capacities of individuals in these

widely varying situations will often be quite different.

Table 6 presents a breakdown of these two types of self-employment, distinguishing between the self-employed whose

businesses are registered for tax or VAT and those whose businesses are not. In 2016, just over three-quarters (77.6 percent)

of the self-employed were involved in businesses that were not registered for either tax or VAT. However, the rate of non-

registration is significantly higher amongst self-employed women, at 84.5 percent. As a result, while women account for 34.5

percent of the self-employed, 37.6 percent of those whose businesses are not registered for tax are women.


Table 6. Registration status of enterprises of the self-employed, 2016

female male Total

number(‘000s)

share(%)

number(‘000s)

share(%)

number(‘000s)

share(%)

Not tax or VAT registered 666 84.5 1 106 73.9 1 772 77.6

Tax or VAT registered 122 15.5 391 26.1 512 22.4

Total 790 100.0 1 496 100.0 2 291 100.0


Note: Figures may not add up due to rounding or unspecified responses.

Table 7 presents estimates of rates of self-employment by gender and race using two data sources. The first, the 2016 LMD

data, covers all self-employment, while the 2013 SESE data is restricted to self-employment in non-tax registered enterprises,

by definition therefore the informal sector. It is estimated that in 2016 almost 2.3 million individuals were self-employed in

South Africa, representing 13.9 percent of total employment. Men were slightly more likely to be self-employed than women

(16.2 percent compared with 11.1 percent), with the gender gap particularly pronounced amongst Asians and Whites. More

than seven out of ten of the self-employed in 2016 were African, with Whites accounting for roughly two out of ten. Thus,

Whites and Asians overall have relatively high rates of self-employment, driven by particularly high rates for men of around

one-quarter. Amongst females, Whites (15.2 percent) and Africans (11.5 percent) have the highest rates of self-employment.

box ii. integrating Women into the formal economy

In South Africa, 29.5 of women are employed in the informal sector and private households, compared with 22.7 of men

(LMD, 2015). This makes women disproportionately more likely to be engaged in employment which is typified by lower

and precarious income, unsafe working conditions and lack of legal protection. In order to integrate women into the

formal labour market—thereby allowing them to access the benefits associated with these opportunities—women need

to participate in the development of policies and regulations which would serve to validate and protect their work and

livelihoods (WIEGO, 2018a). In order to facilitate this, informal workers need to be organised and these organisations need

to be legally recognised and represented in collective bargaining and policy making forums (WIEGO, 2018a).

The challenges to organisation are both specific to local context and similar across various regions. Many informal employers

do not have an obvious employer with which to negotiate. Furthermore, informal employees work for long hours, sometimes

in multiple jobs, which leaves little time for organisation. Competition between informal workers—such as taxi drivers

or street vendors—can also discourage cooperation. Because informal workers are poor—and this is particularly true for

women—there are few resources available to them to cover the costs associated with organisation. In addition, work places

are scattered, and business are small, making organisation difficult (Bonner et al., 2008).

Despite these challenges, there has been an increasing movement worldwide towards informal workers forming

membership-based organisation (MBOs), which serve to allow these workers to use their collective strength to negotiate

better wages and working conditions. When informal organisations are well-organised and recognised by the government,

the results in terms of worker livelihood and integration into the economy can be substantial. For example, waste pickers

around the world are fighting for recognition for their work contributing to the local economy by collecting and recycling

discarded materials. They are often treated as nuisances by authorities, ignored by public policy and face harassment and

exploitation by formal waste collection companies. However, waste pickers in Brazil have found increasing success through

organisation, leading to formal recognition which has enabled better working conditions, space to operate and the right

to bid for government contracts. In the Belo Horizonte municipality, authorities partner with waste picker organisations

to provide infrastructure, education and subsidies for these workers. Waste pickers in Belo Horizonte now enjoy higher

earnings than other informal workers in the municipality (WIEGO, 2018b).



However, once the sample is narrowed to those in non-tax registered enterprises, the picture changes in two key aspects.

First, rates of self-employment for males and females are identical at just over ten percent. Second, self-employment rates are

highest amongst Africans at 12.5 percent, with African women marginally more likely to be self-employed than African men.

As a result, Africans account for almost 90 percent of self-employed women in non-tax registered businesses.

Table 7. self-employment rates by race and gender, 2013 and 2016

african Coloured asian White Total

Total self-employment (‘000s), 2016 1 636 111 98 446 2 291

Male 15.3 8.6 22.8 25.8 16.2

Female 11.5 4.1 9.7 15.2 11.1

Total 13.6 6.5 18.2 21.1 13.9

SESE self-employment (‘000s), 2013 1 371 48 39 85 1 543

Male 12.3 3.0 10.7 4.5 10.3

Female 12.8 3.2 2.6 3.9 10.3

Total 12.5 3.1 7.7 4.2 10.3

Source: StatsSA, Labour Market Dynamics 2016; QLFS 2013Q3; SESE 2013.

Note: Total self-employment figures come from the LMD 2016. SESE self-employment figures refer to employers and the self-employed in non-tax registered enterprises.

The largest cohort of self-employed women, irrespective of youth status, has incomplete secondary education (Figure 6).

Amongst all self-employed women in 2016, 44.0 percent of those under the age of 35 years had incomplete secondary

education, as did 32.9 percent of their older counterparts. Those with matric certificates account for 31.9 percent of youth

and 24.0 percent of non-youth within this group. While older women are relatively evenly spread across the four educational

categories, far fewer women under 35 years report having only primary education (5.8 percent compared with 23.4 percent).

They therefore also have higher shares with either incomplete or complete secondary education. Although the categories

are slightly different, self-employed women are relatively more concentrated than employed women generally in the bottom

two categories. For example, 23.4 percent of non-youth self-employed women have only primary education compared with

16.8 percent of non-youth employed women, while 44.0 percent of self-employed women under 35 years have incomplete

secondary education compared with 30.9 percent for employed women under 35 years.

Once the sample is limited to self-employed women in non-tax registered enterprises as per the SESE 2013 data, the bias

towards lower levels of educational attainment is even clearer. More than seven out of ten of these women has not completed

matric: 71.6 percent amongst youth, and 75.2 percent amongst non-youth.

These patterns of educational attainment for self-employed women highlight the importance of designing incentives that

are accessible to a wide range of women. The relatively poor educational attainment of self-employed women generally,

combined with high levels of attainment for a small subset of these women, implies difficulties with a one-size-fits-all

approach. Importantly, the data suggests that targeting older or younger women may necessitate differentiated approaches

with respect to application procedures and the complexity of incentive structures.


figure 6. educational attainment of self-employed women by youth status, 2013 and 2016

19.6

18.4

24.0

31.9

32.9

44.0

23.4

5.8

6.5

8.6

17.3

19.8

39.3

59.4

35.9

12.2

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0

Tertiary

Comp. Secondary

Inc. Secondary

Primary only

Tertiary

Comp. Secondary

Inc. Secondary

Primary only

LMD 2016 SESE 2013

YouthNon-Youth

Age Group

Percent

Source: StatsSA, Labour Market Dynamics 2016; SESE 2013.

Note: The primary category includes those with no education; the tertiary category includes those with diplomas and/or certificates, and degrees.

Three occupational categories accounted for the majority of self-employed women in 2016. The largest category was

elementary occupations, which accounted for 37.2 percent of self-employed women. This was followed by service and sales

workers (23.5 percent) and managers (16.1 percent). Between them, these three categories accounted for just over three-

quarters of self-employed women. These figures suggest a lack of occupational diversity within the sector and a bias towards

less-skilled occupations, particularly when the diversity of occupations within the managerial category is acknowledged.

Table 8. occupational distribution of self-employed women, 2013 and 2016

self-employed Women (2016)

informal self-employed Women (2013)

number(‘000s)

share(%)

number(‘000s)

share(%)

Managers 127 16.1 - -

Professionals 30 3.8 - -

Technicians & associate professionals 61 7.8 - -

Clerical support workers 13 1.6 - -

Service & sales workers 186 23.5 - -

Skilled agricultural, forestry & fishery workers 10 1.3 - -

Craft & related trades workers 57 7.3 - -

Plant & machine operators 9 1.2 - -

Elementary occupations 294 37.2 - -

Total 790 100.0 - -

Source: StatsSA, Labour Market Dynamics 2016.

Notes: The SESE 2013 dataset does not include data on individuals’ occupations.

Just over half (51.8 percent) of self-employed women are employed within wholesale and retail trade, while a further 20.8

percent fall within CSP services. These two industries account for a combined share of 72.6 percent of self-employed women.



Only two other industries—finance and business services (10.6 percent), and manufacturing (10.4 percent)—account for

more than two percent of self-employed women.

Table 9. Distribution of self-employed women across industry, 2013 and 2016

self-employed Women (2016)

informal self-employed Women (2013)

number(‘000s)

share(%)

number(‘000s)

share(%)

Agriculture, hunting, forestry & fishing 15 2.0 8 1.1

Mining & quarrying 1 0.1 - -

Manufacturing 82 10.4 59 8.5

Electricity, gas & water supply (“Utilities”) - - - -

Construction 12 1.6 2 0.3

Wholesale & retail trade 409 51.8 438 63.8

Transport, storage & communication 15 1.9 12 1.7

Finance & business services 84 10.6 54 7.8

Community, social & personal (CSP) services 165 20.9 115 16.8

Private households 6 0.8 - -

Total 790 100.0 687 100.0Source: StatsSA, Labour Market Dynamics 2016, SESE 2013.

Looking at informal self-employment, it is clear that there is an even greater concentration of women in wholesale and retail

trade and CSP services. Trade alone accounts for almost two-thirds (63.8 percent) of informal self-employment of women,

while CSP services accounts for another 16.8 percent. The shares for all other industries are smaller than those observed for

self-employed women overall.

To construct a more in-depth view of women in informal self-employment, we turn to the nationally representative 2013

Survey of Employers and the Self-Employed (SESE), conducted by Statistics South Africa. As noted, the SESE sample covers

only owners of businesses that are not registered for VAT, meaning that the survey essentially focuses on firms that operate

informally and that it covers informal employers and the informally self-employed.

One of the broader benefits of entrepreneurial activity is the potential for increased demand for labour and, hence, employment.

Table 10 presents a breakdown of self-employment in 2013 according to whether the self-employed are employers, with

at least one employee, or own-account workers. Almost one-third of self-employed men hire other workers (31.2 percent),

compared to fewer than one in six (15.7 percent) self-employed women. While this suggests that female-owned enterprises

may typically be smaller than those owned by men, it also points to a potential difference in motivation: enterprises with no

employees are more likely to be survivalist in nature, with low returns.

Table 10. self-employment type by gender, 2013

female malenumber(‘000s)

share(%)

number(‘000s)

share(%)

Own-account worker (no employees) 579 84.3 589 68.8

Employer (at least one employee) 108 15.7 267 31.2

Total 687 100.0 856 100.0Source: StatsSA, SESE 2013.


Table 11 investigates the extent to which the self-employed are employers, and distinguishes between the paid and unpaid

employees as well as the gender of employees. These firms are clearly small, with the median number of employees being

one for both male and female employers. Female employers, though, do tend to employ fewer people than their male

counterparts. On average, females employ fewer than four employees (0.5 paid males; 1.3 paid females; 0.3 unpaid males;

1.7 unpaid females), while males employ approximately 5.5 employees (1.7 paid males; 3.4 paid females; 0.2 unpaid males;

0.2 unpaid females). Not only do female employers provide employment to fewer people, they are also less likely than male

employers to employ males and more likely to rely on unpaid workers. However, despite their smaller size, a relatively large

proportion of female-owned informal employers report employing between three and nine employees. For example 19.6

percent report employing between three and nine paid males, while 16.2 percent report employing between three and

nine unpaid females. In contrast, only 3.4 percent of male-owned informal employers report employing three to nine unpaid

females (for paid females, the figure is only 3.0 percent).

Table 11. employees of male and female informal employers, 2013

female employers male employersPaid Unpaid Paid Unpaid

males females males females males females males femalesDistribution (%)

0 21.9 65.9 87.9 36.3 87.3 83.8 82.6 77.3

1 38.2 27.6 5.5 37.6 10.5 10.4 15.5 15.6

2 19.4 4.3 3.2 9.4 1.3 2.9 1.7 1.4

3-9 19.6 2.2 2.5 16.2 0.9 3.0 0.3 3.4

10+ 0.9 0.0 0.9 0.4 0.0 0.0 0.0 2.3

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Numbers of Employees

Mean 0.5 1.3 0.3 1.7 1.7 3.4 0.2 0.2

Median 0 1 0 0 1 0 0 0

75th pctile 1 2 0 0 2 0 0 0

90th pctile 1 4 1 1 4 1 1 1Source: StatsSA, SESE 2013.

Lower employment numbers for female-owned enterprises can be explained as a function of lower turnover and weaker

profitability due to concentration in more marginal activities. As many women are forced into or perhaps choose informal self-

employment due to care responsibilities, it is perhaps not surprising that they are tend to rely more heavily on unpaid workers,

who may often be family members or dependents.

According to the SESE data, around two-fifths of the self-employed reported not needing money to start their businesses

(Table 12). Those who did require funding were asked to indicate their main source of funding: their own money, a loan, a

government grant, or some other grant. The majority of those who did need money to start their businesses reported using

their own money: 45.1 percent of women and 44.9 percent of men. Just over one-tenth obtained a loan (13.0 percent of

women and 11.3 percent of men).



Table 12. main source of business funding by gender, 2013

female malenumber (‘000s)

share (%)

number (‘000s)

share (%)

Own money 310 45.1 384 44.9

Loan 9 13.0 97 11.3

Government grant 14 0.2 2 0.2

Other grant 27 0.4 2 0.2

Did not need money to start the business 284 41.3 371 43.4

Total 687 100.0 856 100.0Source: StatsSA, SESE 2013.

Grants of any type are extremely rare, with less than one percent of the self-employed reporting accessing a grant as their

main source of funding. While this is not particularly surprising, given the nature of the sample, it does confirm the very limited

reach of government programmes and funding within the informal sector of the economy.

Amongst those who use their own money to fund their businesses, the survey asks about the source of that money. In this

aspect, there are substantial differences between men and women. Two-thirds (65.9 percent) of men indicate that wage

employment—past or present—was the primary source of this money (Figure 7). In contrast, this was true for only 38.0

percent of women. Men were generally more likely to cite earned or employment-related income (other businesses; sales of

livestock, crops or assets; pensions; or retirement/severance pay) than women, although admittedly these sources are quite

rarely mentioned. This pattern is arguably linked to the generally more favourable position men have within the labour market,

enabling them to source funds in this way.

figure 7. main source of own money for business funding by gender, 2013

36.28.9

11.31.4

0.00.3

2.45.9

2.15.5

4.12.12.0

3.31.2

2.52.6

4.138.0

65.9

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0Percent

Other savings

Stokvel payout

Matured investment policy

Retirement/severance pay

Pension from work

Inheritance

Sales of other assets

Sale of livestock/crops

Other business

Wage employment

MaleFemale

Gender

Source: StatsSA, SESE 2013.

Note: ‘Wage employment’ refers to previous and/or present wage employment.

For women, the most commonly cited source of money was from savings, whether in the form of a stokvel payout (11.3

percent) or from other savings (36.2 percent). In other words, almost half of women who used their own money to start a

business cited savings as the primary source of that money, compared to one-tenth of men.


Survey respondents were also asked as to the reason for not registering their businesses (Table 13). Within the sample, 9.3

percent of businesses were registered for income tax, but none were registered for VAT (by design). The registration rates for

males was almost twice that of females, but was still only 11.6 percent. Interestingly, few respondents cited onerous registration

processes as their main reason for non-registration: just 5.2 percent in terms of income tax registration and 4.4 percent in terms

of VAT registration. Instead, between two-thirds and three-quarters of respondents indicated that their businesses did not

meet registration requirements. Here, the proportion was slightly higher for VAT registration than for income tax registration

and, while there was no real gender difference for the former, relatively more females than males indicated their businesses

did not meet income tax registration requirements.

Table 13. Reasons for non-registration of business by gender, 2013

income Tax Registration vaT Registrationfemale male Total female male Total

Proportion of businesses registered 6.5 11.6 9.3 0.0 0.0 0.0

Reasons for non-registration

Business does not meet registration requirements 70.2 67.7 68.8 72.8 73.0 72.9

Didn’t know that business had to be registered 23.8 20.1 21.8 21.6 16.3 18.7

Registration process too tedious/complicated 3.4 6.8 5.2 3.4 5.2 4.4

Other 2.6 5.4 4.1 2.2 5.5 4.0

Total 100.0 100.0 100.0 100.0 100.0 100.0

Source: StatsSA, SESE 2013.

Although in the minority, a significant proportion of respondents indicated that they did not know that their businesses

needed to be registered. This was a slightly more common response amongst women than men, and for income tax rather

than VAT registration. This may suggest that more work may need to be done to inform informal business owners that they

should register their businesses. However, it is quite possible that this may just shift respondents into the first category

(‘business does not meet requirements’).

That such a large proportion of businesses do not meet registration requirements points to a potential gap in support for

informal businesses. Without registering, they are ineligible to apply for support; but without support, they may never be in

a position to register. Further, although few respondents cite process-issues as a reason for non-registration, this figure may

very well change once respondents actually try to register their businesses. In this context, initiatives to further simplify these

processes should not be discounted.

3.1.5. Unemployment

To contextualise women’s position within the labour market, Figure 8 presents the female share of three key labour market

aggregates—the narrow labour force, employment and narrow unemployment—over the past decade. While women

account for just over half (50.5 percent) of the working-age population in 2018, they are outnumbered by men within all three

aggregates. Women account for approximately 45 percent of the narrow labour force, a proportion that has remained within a

one percentage point range throughout the decade. Importantly, though, just under 44 percent of the employed are women.

Here too, the proportion has remained remarkably stable.

The consequence of women accounting for an even smaller share of employment than they do of the narrow labour force is

that their share of narrow unemployment is considerably higher. In the second quarter of 2018, women accounted for 49.1

percent of the unemployed, 5.3 percentage points higher than their share of employment. Within unemployment, the share

of women is marginally more volatile, with women even forming the majority of the unemployed in 2008.



Figure 9 explores the differences in narrow unemployment rates between men and women in more detail, disaggregating

by race, age group, educational attainment and location. It is worth recalling that, as shown in Table 2, the official (narrow)

unemployment rate in the second quarter of 2018 was 27.2 percent; amongst men, 25.3 percent were unemployed compared

to 29.5 percent amongst women. For virtually all groups, unemployment rates amongst women are higher than those for men,

and often by a substantial margin. For example, relative to those of males, female unemployment rates amongst 15-24 year olds

are 9.5 percentage points higher; they are also 6.1 percentage points higher amongst 25-34 year olds, 5.7 percentage points

higher amongst those with incomplete secondary education, 5.0 percentage points higher amongst Africans. Exceptions to

this pattern are found amongst Coloureds, Whites, and 55-64 year olds; in each case, though, the difference is marginal.

figure 8. female labour force, employment and unemployment shares, 2008-2018

45.1

44.8

44.6 45.0

44.8 45.1

45.2

45.2

45.0

45.3

45.2

43.0 43

.643

.243

.443

.543

.843

.943

.843

.4 44.0

43.8

52.3

48.8

48.6 49

.548

.5 49.1

48.8 49.3

49.2

48.7 49.1

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0

55.0

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

Narrow labour force Employment Narrow unemployment

Fema

le sh

are (p

ercen

t)

Source: Own calculations, StatsSA, Quarterly Labour Force Surveys, various years.

Notes: Estimates are from the second quarter surveys in each year.


figure 9. narrow unemployment rates by gender, 2018

28.233.2

23.6 22.9

9.4 12.28.5 7.4

49.5

59.0

30.937.0

18.924.2

15.7 16.310.6 8.7

23.4 26.331.7

37.4

25.831.4

15.2 18.1

4.98.9

24.428.8 28.0

31.9

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

African Coloured Asian White 15-24 yrs 25-34 yrs 35-44 yrs 45-54 yrs 55-64 yrs

Primary Inc. Sec. Comp. Sec. Dipl/Cert Degree Urban Rural

Race Age

Educational Attainment Location

MaleFemale

Perce

nt

Source: StatsSA, Quarterly Labour Force Survey 2018Q2.

Notes: Details for expanded unemployment rates can be found in Figure A 1 in the appendix.

Unemployment rates for both males and females, though, exhibit the same patterns across these covariates. Unemployment

rates are highest amongst African and Coloureds, and lowest amongst Asians and Whites; they are highest amongst the youth

and lowest amongst the oldest working-age cohorts; they are highest amongst those with lower levels of education, and

lowest amongst those with tertiary qualifications; and they are lower in urban than in rural areas. The pattern of unemployment

rates across educational categories is, perhaps, somewhat unexpected with primary-educated individuals experiencing lower

rates of unemployment than those with either incomplete or complete secondary education. However, individuals with only

primary education also tend to be older, and older individuals have lower rates of unemployment. It is therefore important to

remember that numerous factors influence the likelihood of unemployment at the individual level, and that an understanding

of unemployment in a multivariate context is required for a more accurate assessment of the risk factors and their relative

importance.

3.2. Constraints to smme growth and entrepreneurship in south africa

Small, Medium and Micro Enterprises (SMMEs) have been identified as a key component to advancing inclusive growth and

development in South Africa. In the National Development Plan, government highlights the importance of these businesses

for job creation, innovation and competitiveness, with the goal that 90 percent of new jobs will be created by SMMEs in South

Africa by 2030. The successful entry and growth of these firms may create a sustainable mechanism through which the wages

of those at the bottom of the wage distribution can be increased and the level of inequality reduced. Entrepreneurship has

often been presented as an alternative for the unemployed who are unable to be absorbed into formal employment. This view

is supported by the international literature. For example, Van Praag and Versloot (2007), in a systematic review of 56 studies,

find that entrepreneurs are an important source of job creation and that there are positive, long-term spill-over effects to

entrepreneurship which serve to increase employment growth rates. Furthermore, supporting the growth of existing SMMEs

could serve to encourage innovation and employment creation in these businesses.

The extent to which SMMEs, and entrepreneurship particularly, have been harnessed to increase employment and reduce

inequality in South Africa has been disappointing. In low-income countries, formal and informal SMMEs contribute over 70

percent to employment and 60 percent to GDP; in middle-income countries, the SMME contribution to employment and GDP



is higher, at 95 percent and 70 percent respectively (Ayyagari et al., 2003). In contrast, South African SMMEs employ around 56

percent of the workforce (DTI, 2008) and contribute an estimated 45 percent to 50 percent to GDP (DTI, 2004).

box iii. informality in Context

South Africa is relatively unique in the developing country context in that the informal sector is unable to act as a successful

buffer against unemployment. In many developing countries, the unemployment rate is low as many low-skilled workers

are employed in the informal sector, mostly in survivalist enterprises. In South Africa, however, there are barriers to entry

into the informal sector and this, coupled with a shortage of employment opportunities in the formal sector, leaves the

unemployed with few opportunities to earn an income. These informal sector barriers in South Africa have historical roots.

Apartheid-era legislation enforced spatial segregation leaving many black South Africans in informal settlements, separated

from the city centre and geographically distant from labour market opportunities. In addition, relatively high levels of labour

law enforcement in South Africa may be hampering growth in informal activities (Fernandez et al., 2017).

South Africa has a relatively low rate of informality, with only 29 percent of individuals in informal employment. This is

less than half the average informality rate for sub-Saharan Africa, and well below the informality rate of many developing

regions. In the absence of formal sector job creation, there is a dire need to put in place policies that serve to increase

participation in the informal sector, because for many labour market participants informal sector employment may be a

realisable alternative to unemployment. Successful policies that promote access to and growth in the informal sector could

potentially serve to decrease inequality by absorbing marginalised individuals into employment.

Table ii.1. informality rates by region

Region/Country Informal Employment as share of Non-Agriculture Employment (%)Latin America & the Caribbean 51Sub-Saharan Africa 66Middle East & North Africa 45Eastern Europe & Central Asia 10South Asia 82East & South-East Asia & Pacific Islands 65China 33South Africa 29

Source: Vanek et al. 2014, authors’ own calculations. For South Africa, QLFS 2016Q3.

Concentrating on entrepreneurship particularly, Table 13 gives the proportion of the population aged between 18 and 64

years who are engaged in various levels of entrepreneurial activities, using the Global Entrepreneurship Monitor (GEM) data

for 2015. This table shows that South Africa ranks poorly in all three measures of entrepreneurial activity. South Africa’s Nascent

Entrepreneurship Rate4 is 5.5 percent, its New Business Ownership Rate5 is 4.9 percent and its Established Business Ownership

Rate6 is 5.0 percent, placing it 35th, 32nd and 53rd out of the 60 countries studies, respectively. All three of these rates are

lower than the regional averages for Africa, Asia and Latin America, indicating that levels of entrepreneurship in South Africa

lag behind other developing country regions.

4 The Nascent Entrepreneurship Rate is the proportion of 18 to 64 year olds setting up new businesses.

5 The New Business Ownership Rate is defined as the proportion of 18 to 64 year olds owning businesses that are no older than 3.5 years.

6 The Established Business Ownership Rate refers to the proportion of 18 to 64 year olds who own businesses that are older than 3.5 years.


Table 14. share of 18-64 year olds engaged in entrepreneurial activity, by region

Region/Country nascent entrepreneurship Rate (%)

new business ownership Rate (%)

established business ownership Rate (%)

Africa 12.5 7.9 10.1

Asia & Oceania 6.0 7.4 10.4

Latina America & the Caribbean 12.9 7.5 8.5

Europe 4.8 3.1 6.6

North America 9.0 4.8 8.1

South Africa 5.5 4.9 5.0

Rank (out of 60) 35th 32nd 53rd

Source: GEM (2016).

Notes: The Nascent Entrepreneurship rate is the proportion of 18-64 year olds setting up new businesses; the New Business Ownership Rate is the proportion of 18-64 year olds owning businesses that are no older than 3.5 years; the Established Business Ownership Rate is the proportion of 18-64 year olds owning businesses older than 3.5 years.

FinScope (2011) finds that access to credit and access to affordable credit are amongst the most regularly reported obstacles

for growth amongst SMME owners. They find that approximately 42 percent of SMME owners are financially excluded—

meaning they do not use any formal or informal financial products or services, and that any saving that does occur happens at

home, while any borrowing is from friends or family. This difficulty for small business owners in gaining access to credit is likely

due to the conservative lending practices of banks. In deciding whether to provide credit to an entrepreneur or business—and

the rate at which credit is offered—banks rely on the credit risk profile of the owner or business. There are various factors which

contribute to the high credit risk profiles for SMME entrepreneurs, including no alternative income sources, unsustainable

income streams, poor business and financial management skills, and a lack of risk mitigation strategies. These factors make

SMME entrepreneurs unattractive to formal lenders, where the perceived risk of defaulting is high.

In addition, access to land is a constraint on entrepreneurship. Not only is land used as collateral for finance, in order for

business to develop and grow, business needs access to affordable premises that is close enough to workers, the market, and

that is safe and suitable for work. FinScope (2011) identifies “space to operate” as the largest obstacle for small business growth,

particularly in Gauteng. Transport infrastructure is needed to reach the major economic hubs and to access their respective

markets. This is particularly important in South Africa, where due to the entrenched problem of spatial mismatch, millions of

labour market participants are located significant distances from the urban centres. Naudé (2008) finds that distance from the

city centre is an important factor in explaining African unemployment rates in South Africa, while for White South Africans

distance is not important. This is significant because Africans are most likely to own small businesses, presenting an alternative

to unemployment for this group. Thus, any constraints relating to spatial mismatch will impact on SMMEs, specifically African-

owned SMMEs. This spatial dislocation between the labour force and the economy results in challenges for SMMEs. For

example, SMME owners and potential entrepreneurs (particularly those amongst the unemployed) will find it relatively costly

to travel to the economic hubs for business purposes, and these are the areas where their businesses are most likely to grow

and mature. Thus, effective and affordable transport infrastructure is an important factor for SMME development in South

Africa.

Table 15 summarises some of the barriers to accessing credit and the particular gender-specific constraints faced by women in

this regard. These include constraints due to traditional norms which exclude women from accumulating assets and property,

employment and income limitations, exclusions from financial and economic decision making and adverse attitudes towards

women. The lack of financial literacy of women compared to that of men is also a major barrier that prevents women from

being able to access credit in South Africa. A 2014 study found that South African women score significantly lower than men

in areas of financial control, financial planning, choosing financial products, and general knowledge and understanding of

finance (Roberts, Struwig and Gordon 2014). This means that women may be unable to improve their economic situation



if they are unaware of the financial products which are available to them (Roberts, Struwig and Gordon 2014). Therefore,

it is vital to improve financial literacy for women in order to empower them to use financial products for the promotion of

entrepreneurship and other economic activities.

This is summarised in a quote from a study by the International Finance Corporation, which highlights “the need for a more

deliberate and integrated strategy focusing on women in business. Since women are the largest group of entrepreneurs in the

country, gender-focused business strategies must inform all BEE and financial access measures. Institutions which act now to

better understand and service this large, growing segment of South Africa’s business population will reap the benefit in the

future” (World Bank, 2006).

Overall, it is clear that when assessing the constraints to small business growth and entrepreneurship in South Africa, it is

important to take into account the extent to which these constraints disproportionately affect women. For example, while

policies enhancing access to credit are important for both the creation and growth of SMMEs, these interventions will

disproportionately support men if the gender-specific constraints to accessing finance for women are not also addressed.

Table 15. barriers to credit for women and their effects

barrier effects

Legal constraints The traditional norms and values prevent women from leaving formal financial options acting as legal persona and from accumulating assets such as property. Such constraints impact on women’s ability to offer assets as collateral which is often beyond the scope of a women’s available or limited assets. Women are still treated as legal minors in some communities constraining their ability to make independent decisions or contractual arrangements e.g. for funding.

Employment and income limitations faced by women

Women are still most likely to be employed at the lower levels, least skilled, least influential and lowest paid jobs in the economy and this also impacts negatively on their ability to accumulate assets and equity.

Exclusion from policymaking, decisions and influence in financial and economic decision-making

South Africa has largely excluded women from decision-making in both the economic and financial spheres of influence. Since women are largely not in positions of power in these segments of society, this has the effect of not fostering a culture which recognises the gender constraints and respects the needs of women.

Women are likely to need start-up capital which for commercial institutions are high risk and therefore not supported by gender neutral institutions insensitive to the gender constraints faced by women and there is also very little attempt made to explore alternative risk management strategies better suited to the asset limitations of women.

Attitudes towards women Male decision-makers often consider the realities of women’s lives as adverse and use the multiple roles women play as a justification for declining business credit. In a situation of scarce resources, investors will often go with what they know i.e. men.

Lack of information and exposure to business and finance environments

Women are often not aware of the financial or non-financial support available to them to enhance their business aspirations.

Business maturity and financial institution policies

Whilst men and women face difficulties when setting up businesses, women face additional difficulties such as access to finance. The playing field tends to level out when women’s business reach maturity and are able to provide sufficient evidence to reduce the perception of risk associated with gender.

Lack of collateral means that the primary source of funding for resource-poor women is high interest bearing and low value micro finance.

Banks are mostly not aware that women face gender specific constraints when seeking finance and may adopt a gender neutral position, assuming that this puts women on an equal footing.

Women often want to borrow smaller amounts and this may be outside of the minimum loan policies of a bank.

Source: DoW (2015), sourced from Southern Africa Gender Protocol Alliance (2015).


4. inCenTive PRogRammes as a PoliCY insTRUmenT

4.1 Review of selected international incentive Programmes

4.1.1. Country Contexts

Having considered the particular socioeconomic context within which South African women find themselves, we now

consider four countries at different levels of development that potentially have experiences of incentive schemes from which

South Africa could learn.

In this international review of incentives schemes we restrict our choice of countries to those referred to in the national

evaluation undertaken by the Department of Planning, Monitoring and Evaluation (DPME) for ease of comparison across

both reports. The four selected countries, namely Chile, Ethiopia, Germany and Thailand, are also distributed across the

development ladder. First, Ethiopia is the least developed economy of the group and, although at a lower level of development

than South Africa, could potentially offer valuable lessons from its successes related to the provision of access to a population

characterised as mainly unskilled. Second, Thailand is a middle-income country with a substantial manufacturing sector

in terms of contribution to GDP (27.4 percent in 2016, twice the size of wholesale and retail trade and four times that of

agriculture) and employment (16 percent, only surpassed by agriculture’s 31 percent) (Diao, McMillan and Rodrik, 2017), offers

potential lessons for South Africa on how to harness entrepreneurship as an avenue for employment creation. Third, Chile,

which although a high-income country shares similarities with South Africa, in that it has high income inequality and a dual

economy where a very structured formal economy contrasts with a fully-fledged informal economy. Fourth, Germany, being

the most developed in the group, could potentially offer lessons on the nature of support that South Africa could aim to offer

its women as it advances developmentally.

While South Africa’s particular history has, as already discussed, given rise to a set of labour market characteristics that can be

described as uniquely South African, it does share certain similarities with each of the four selected countries. Table 16 presents

several economic and labour market statistics for each of the five countries.

Five characteristics of the countries under review emerge from Table 16. Firstly, of the five countries, Germany has the highest

per capita income and Ethiopia the lowest. Except for Ethiopia, the economies of the selected countries have similar structures

in that the services sector accounts for the largest proportion of total GDP. In contrast, Ethiopia is substantially more dependent

on agriculture, which accounts for 37.2 percent of that country’s GDP. Secondly, there is relatively wide variation in labour force

participation rates across the four countries. Ethiopia has the highest participation rate, which at 82.0 percent is 27 percentage

points higher than last-placed South Africa’s. In each of the five countries, participation rates amongst females are substantially

lower than those of males. This gender gap in participation ranges from 10.8 percentage points in Ethiopia to 24.0 percentage

points in Chile.

Thirdly, South Africa’s unemployment rate is by far the highest of the five countries under review; at 27.3 percent, the country’s

unemployment rate is almost four times that of second-placed Chile (6.9 percent). In three of the five countries, women are

more likely to be unemployed than men; however, in Thailand, unemployment rates are identical for men and for women,

while German men are slightly more likely to be unemployed than German women. Fourthly, vulnerable employment is

significantly more prevalent in Thailand and Ethiopia than elsewhere, but is least common in Germany and South Africa.

Vulnerable employment refers to own account workers and contributing family workers, and its prevalence is linked to the

extent of the informal sector. Workers in vulnerable employment tend to have low wages and often have very insecure terms of

employment. Women are more likely to be classified as employed under vulnerable working conditions than men in Ethiopia,

Thailand and Chile, although this is not the case for South Africa and Germany.



Table 16. Key indicators for Chile, ethiopia, germany, Thailand and south africa, 2017

indicator Chile ethiopia germany Thailand south africa

GNI per capita, PPP (current international $) 22 540 1 730 49 690 16 070 12 830

Value added (% of GDP)

Agriculture 4.3 37.2 0.6 8.3 2.4

Industry 31.3 21.3 30.5 35.8 28.9

Services 64.4 41.5 68.9 55.9 68.7

Labour Force Participation Rate (LFPR) (% of population aged 15+)

Total 62.0 82.0 60.0 69.0 55.0

Female 50.4 77.0 55.0 60.7 48.0

Male 74.3 87.8 66.3 77.5 62.0

Unemployment rate (%)

Total 6.9 5.4 3.8 1.0 27.3

Female 7.5 8.1 3.5 1.0 30.3

Male 6.4 3.0 4.0 1.0 24.9

Vulnerable employment (% of total employment)

Total 24.0 48.0 6.0 51.0 9.0

Female 25.0 51.0 5.0 53.0 9.0

Male 23.0 46.0 7.0 50.0 9.0

Urban Population (% of total) 90.0 20.0 76.0 52.0 65.0

Population in urban agglomerations of more than 1 million (% of total population)

36.5 3.2 9.6 16.6 37.0

Source: World Bank Development Indicators (World Bank, 2018)

Notes: 1. Employment figures are ILO modelled estimates, not national estimates. 2. The South African figures in this section differ slightly from those provided elsewhere in this report as they relate to a different period. The figures are provided for a similar period in this section to allow for greater evaluation with the comparator countries.

Lastly, the majority of the populations in each of the countries, except Ethiopia, reside in urban areas. In Ethiopia, the

urbanisation rate is only 20 percent, compared with 65.0 percent in South African and 90.0 percent in Chile. A further indicator

of the level of urbanisation is the share of the population living in urban agglomerations of 1 million. Due to variations in the

definition of urban and rural areas, the United Nations Population Division utilises the urban agglomeration measure that

refers to the actual population residing within the boundaries of adjoining territory inhabited at urban density levels without

referring to any administrative boundaries (World Bank, 2017). Examples of well-known urban agglomerations include Tokyo,

New York City, Mexico City, New Delhi, and Seoul – Lagos and Kinshasa are Africa’s largest urban agglomerations (World Bank,

2017). According to this measure, the populations of Ethiopia, Germany and Thailand are considerably less concentrated in

large urban agglomerations than is the case in Chile and South Africa.

Having compared the structure of the economies and the labour market status of women across the five countries, we turn

now to a summary of the incentive programmes in the four comparator countries. The aim here is to describe the nature

and performance of incentive schemes and women’s empowerment initiatives in the selected countries. In selecting

programmes or policies to discuss in this section, we defined incentive schemes to include any financial and non-financial

support that is targeted at a sector, business or type of individual with the intention of growing the economy, developing

skills and promoting access to markets.7 A key observation relating to the choice of incentive programmes selected is that the

programmes discussed seek to explicitly empower women in that only women-owned businesses qualify to apply, or they

indirectly empower women where they are focused in sectors where women form the large majority of workers. For a fuller

7 Source: https://www.thedti.gov.za/financial_assistance/docs/incentive_booklet2012-2013.pdf (Last Accessed: 15 February, 2018).


discussion of the entire spectrum of incentive programmes present in these countries, interested readers should refer to the

DPME national evaluation report (DNA Economics, Department of Policy, Monitoring and Evaluation and Rebel, 2017). The

objective of this section of the report therefore is to draw lessons from these countries with respect to programme design and

evaluation.

4.1.2. Chile

Overall, Chile has a relatively low LFPR whereby six out of ten working age individuals are active in the labour force (Table 16).

Despite this observed gender gap, Chilean women have increased labour force participation from 32.1 percent in 1990 to 50.4

percent in 2016 (World Bank, 2018). This was achieved through targeted government policies and programmes to improve the

socioeconomic profile of women in Chile. Although women have joined the labour force in greater numbers, their participation

rates remain low compared to comparator OECD and Latin American countries (Olaberría, 2016). Furthermore, greater female

participation in the labour market is constrained by economic, cultural and regulatory barriers (Olaberría, 2016). For instance,

where employed, women often work in low-paying occupations or sectors such as services, health and social work, often

working part-time or dropping out of the labour force entirely after becoming mothers. Low earnings and significant absences

from the labour market increase the risk of old age poverty for women (Olaberría, 2016).

4.1.2.1. Women-Specific Initiatives

In 2010, Chile established the first publicly funded start up accelerator, Start-Up Chile. The entirely government-funded

initiative seeks to attract new technology start-ups that will position Chile as the innovation and entrepreneurship hub of

South America (Karsten and West, 2016). Modelled along the lines of Silicon Valley, the hub is often referred to as “Chilecon”

Valley.8 Following each call for applications, 100 start-ups from all over the world are chosen for the six-month program. Each

participant receives US$ 45 000 in equity-free funding, a six- to twelve-month temporary visa, office space, and opportunities

for networking and coaching.9 In return, the budding start-ups must earn 4 000 “social capital points” by hosting various events,

mentoring and sharing knowledge that will engage the local population in entrepreneurship, technology, and innovation

(Karsten and West, 2016).

As of 2016, it was estimated that more than 1 200 start-ups from 72 countries had graduated from Start-up Chile, although it is

unclear what proportion of women are represented by this figure (Karsten and West, 2016). The programme participants have

raised over US$100 million and created more than 1 500 jobs (Karsten and West, 2016). Invariably, thousands of Chileans have

benefited from the community outreach initiatives organised by participating companies. Despite its growth and success,

the programme has struggled to retain participating firms in Santiago as many of the programme participants relocate to the

United States (Karsten and West, 2016). This is the case as Chile has a shortage of venture capitalist funds and a small consumer

market for the software and technology which limits overall growth.

While the Start-Up Chile initiative is not targeted exclusively at women, the “S Factory” is a pre-accelerator programme

directed at female entrepreneurs still in the ideation business phase and provides a US$14 000 grant and 12-week mentorship

opportunity.7 The establishment of this female focused grant followed the low application and/or qualification rates of high-

impact female entrepreneurs. Companies with a functional product qualify for “Seed” funding of US$ 30 000 over six months.

Top performing companies that are locally incorporated but desiring to expand into the region or globally may qualify for US$

90 000 to pursue further growth.

In addition to the S Factory, Chilean female business owners wishing to develop their expertise or develop innovative product

solutions can apply for further financing from 2016 onward. Thirty-five pre-selected beneficiaries are awarded roughly US$

7 500 to assist with the provision of technology or their skill development. This financing instrument is established with the

8 Source: https://techcrunch.com/2016/10/16/a-look-into-chiles-innovative-startup-government/ (Last Accessed: 25 January 2018).

9 Source: http://www.startupchile.org/programs/the-s-factory/ (Last Accessed: 25 January 2018).



further intention of bridging the gap between the supply of knowledge providers’ services and the needs of companies and

the market and is part of the Gender Agenda.10 This is a far-reaching set of policies and programmes intended to bridge the

Chilean gender gap. Focus areas will include, but not be limited to, the following: the design of educational reforms; the

electoral system; labour policies; the New Political Constitution; the National Investment System; the design of the national

system of care; and the reform of the nursery regime for children of workers.

The creation of the Ministry of Women and Gender Equity in 2014 is another major step in implementing the Chilean Gender

Agenda. This ministry is currently providing support to legislative initiatives aimed at combating gender-based violence in

Chile, improving the low rates of employment among women and “mainstreaming the gender perspective across the other

government sectors and programmes”.

One of the key programmes of the Ministry of Women and Gender Equity to improve employment and labour market outcomes

is the “Women, Associativity and Entrepreneurship Programme”. The programmes’ objective is to increase the number and

visibility of female entrepreneurs, strengthening the entrepreneurial skills of women to contribute to the sustainability of their

businesses and their potential growth. An oversight that is likely to affect overall performance is that the programme does

not have designated funding, so the priority actions are restricted to the coordination of different State programs and the

Ministry’s regional offices.

4.1.2.2. Other Relevant Initiatives

As the Chilean economy has grown more sophisticated, developing innovation has become an explicit policy goal (Agosin

et al., 2010). In line with this, initiatives to empower individuals have been aligned to the innovation drive. We have already

considered a few initiatives in this space targeted at females. However, women can access any of the other innovation

initiatives not specifically targeted to them as well. One of the key programmes coordinated by Corporación de Fomento de la

Producción de Chile (CORFO)11 is the “Startup Journey”. Through this initiative CORFO funds more than 50 different distribution

points, which refers to anything from incubators to co-working spaces. Participants also have access to over 1 000 mentors

located across the country. CORFO monitors the performance of distribution points’ closely through a system that certifies

every step of the acceleration process. For instance, if a distribution point seeks government funding, it needs to obtain a

certificate showing that it met predetermined growth targets.

Despite having overall business-friendly regulations, a relatively stable economy and this explicit innovation drive, Chile lacks

a substantial entrepreneurial spirit amongst its young people (Karsten and West, 2016). In addition, where investments are

made, they are often clustered in the capital city, Santiago, with the result that growth is skewed geographically. Consequently,

promoting small business growth and development in far-flung regions has become a growth priority for Chile and initiatives

toward this end are particularly relevant to increasing the participation and empowerment of women within the Chilean

economy.

The Gerencia de Fomento runs programmes that aim to promote small firms. They seek to upgrade the quality of production to

allow firms to access large firms’ supply chains. They also enable small and medium firms to access and adopt new technology.

They operate based on the matching grant principle, with CORFO’s contribution constituting normally up to 50 percent of

the costs, with a maximum amount per firm and per programme (Agosin et al., 2010). Funds are not provided directly to

beneficiaries, they are disbursed to regional offices and applications made at the local level.

CORFO has a development finance institution, Gerencia de Intermediación Financianciera (GIF), that manages 13 different

finance products, most of which are aimed at providing long-term, investment-oriented loans to SMEs. The key objective of

this incentive is to relieve financial constraints perceived to be stifling the growth and development of small and medium

10 Source: https://portal.sernam.cl/?m=programa&i=72 (Last Accessed: 27 January 2018).

11 CORFO is a Chilean governmental organistion that was founded in 1939 promote economic growth in Chile. As the economy has advanced, its focus has shifted to adjust with the current focus being innovation and in particular, start up innovation.


businesses. These funds are not directed at a specific sector or type of recipient meaning that anyone may apply if they meet

the application criteria. Relative to the funding needs of SMEs, GIF’s finance portfolio remains small. This is also the case when

compared against other donor banks within the region.

The Small Business Guarantee Fund (Fondo de Garantía para Pequeños Empresarios - FOGAPE) was launched in 2000. It seeks

to guarantee a certain percentage of the credit granted by public or private financial institutions to small and micro firms,

small exporters, and small business associations. Access to these funds has increased the share of small and micro firms with

a bank account is estimated at over 90 percent in 2007 (Agosin et al.,2010).

4.1.2.3. Summary

Access to credit and funding is identified as a significant barrier to the growth and development of entrepreneurs globally.

Therefore, it is important to match potential beneficiaries correctly to the incentive that would best meet their own business

needs and ensure the overall sustainability of the financial institutions to ensure that further groups of entrepreneurs also gain

access to funds.

Furthermore, where funds are awarded, it is important to ensure that the values granted, and the length of the support are

commensurate with growth and business needs. Critics of some of the Chilean programmes have pointed out the fact that

the level of funds that have been awarded have far exceeded the number of jobs created and that where funding has stopped,

many firms have relocated or shut down, indicating that the funds were critical to the existence or survival of the firm (Karsten

and West, 2016).

Lastly, another similarity between the Chilean and South African incentive landscape is that there are few incentives that are

specifically designated for female entrepreneurs. Hence, male and female entrepreneurs may apply to any of the discussed

incentive schemes to access funding, mentoring opportunities and other support. This reality varies significantly from the

current Chilean governments’ rhetoric of seeking to bridge the widening socio-economic gender gap. As with the South

African setting, while we have noted that women have benefited from the broader Chilean innovation policy agenda, it

is important to consider a set of incentives targeted at women that will attract and retain females, thus increasing overall

participation and lowering poverty and inequality. In this way, national policy agendas can have a greater impact on the

individuals most in need of assistance.

4.1.3. ethiopia

As the data in Table 16 indicates, there is a significant number of Ethiopian women who are active in the labour force but who

have not secured wage employment and are most likely engaging in unpaid work. Additionally, the informal sector, which is

characterised by small low productivity firms, dominates the Ethiopian economy. The informal sector plays an important role

for women in the labour market: women account for three-fifths of those engaged in the sector (Brixiova et al., 2010; Kinpin,

2013).


A significant proportion of the women-specific initiatives hinge on increasing access to finance, credit and other assets such

as land. This follows the cultural and legal barriers that limited women’s ability to access these resources.12 One of the main

development and governance schemes is the Growth and Transformation Plan (GTP), whose objective is strengthening

associations and domestic firms as well as encouraging increased participation and the accumulation of equity by women

and youth. In its first phase of implementation, this policy ensured that more women engaged in and benefited from both

agricultural and non-agricultural activities and that they gained access to savings and credit and other non-financial support

(GTP, 2015). Most remarkably, the proportion of women who received land right certificates increased (GTP, 2015).

12 These include the prevalence of patriarchal customary laws, the absence of legal representation for women, cultural bias in the allocation of land and an unequal labour law framework (World Bank, 1998).



In addition to the publicly-funded initiatives, there are some private sector led schemes which specifically target Ethiopian

women. We consider two of these: the Development Credit Authority (DCA) guarantee in partnership with the United

States Agency for International Development (USAID), and the Women’s Entrepreneurship Development Project (WEDP) in

partnership with the World Bank.

The DCA, undertaken by USAID and the Bank of Abyssinia, was finalised in 2008 to provide women-owned small and medium

enterprises (SMEs) with credit assistance by guaranteeing up to US$4.3 million in loans over the period 2008 to 2014 (Kipnis,

2013). The aim of the DCA guarantee was to promote gender integration, accelerate income and employment creation, and

complement USAID’s activities in trade, investment and private sector competitiveness. Kipnis (2013) observes that the DCA

guarantee has improved the access of women-owned SMEs to finance as businesses that previously lacked collateral may now

apply for loans and be considered for funding. This increases women’s ability to participate in the economy and potentially to

transition from the informal to the formal sector.

Moreover, female entrepreneurs face more challenges in accessing finance relative to their male counterparts (GERA, 2017),

an issue that the WEDP seeks to address by bridging the financing gap faced by women-owned enterprises. The intention

of this intervention is that the earnings and employment levels at female-owned enterprises will increase. Strobbe et al.

(2015) summarise the WEDP programme as using incentives to help the Development Bank of Ethiopia to package subsidiary

loans and related technical support to participating microfinance institutions that would in turn develop and provide loans

to successful micro and small firms. This initiative has targeted underserved women who previously lacked access to credit,

pointing to the potential of public-private partnerships to deliver fruitful outcomes in this area.


The Ethiopian government has implemented various fiscal and non-fiscal schemes as part of the GTP development objectives.

Three main interventions are considered here, namely the investment incentive scheme, the tax incentive scheme and the

export trade duty incentive scheme.

Ayele (2006) notes four objectives of the investment incentive scheme: firstly, to use domestic resources efficiently; secondly

to introduce science and technological advancement; thirdly, to create employment opportunities; and lastly to balance

inter-regional development. The author investigated the impact of the investment incentive programme on the expansion of

enterprise start-ups in assisted industries and locations and found no causal effect. Nonetheless, the supported indigenous

projects were observed to be in and around Addis Ababa (Ayele, 2006). This correlation between supported projects and their

location in Addis Ababa highlights the low start-up costs for businesses located around the main business centre of Addis

Ababa. In addition, as previously indicated, Ethiopia is largely rural, with four out of five individuals residing in rural areas where

access to basic infrastructure is even less common (WDI, 2016).

The tax incentive scheme relieves beneficiaries from paying income tax (based on a schedule) and has had a positive impact

in attracting additional investment, employment creation and increasing long-term government revenue (Gebremedhin et

al. 2016). Despite the positive outcomes of the programme, this incentive scheme is not targeted specifically at women. This

is the case as a clear majority of women-owned enterprises are small (providing work for the owner only or for the owner and

a handful of employees) and are mainly located in the informal sector. For government to effectively reach most women, the

incentive scheme should be sector-specific or stipulate a level of female ownership.

The export and trade duty incentive scheme aims to create a conducive environment for domestic products to access the

global commodity markets (Export Trade Duty Incentive Schemes, 2012). Regassa (2008) investigated the impact of the export

trade duty incentive scheme and highlighted a positive effect of this scheme on exports. As with the programmes already

discussed, this scheme does not explicitly target women as Ethiopian exports are mainly capital intensive and depend on bulk

raw materials to produce their final outputs. As this is not the typical profile of female-owned businesses, women are once

again locked out of these incentive schemes.


4.1.3.3. Summary

In terms of structure, the Ethiopian economy greatly differs from South Africa’s: the former is mainly agrarian and less

transformed relative to the latter, which is services-driven and more sophisticated. However, despite these different phases of

development, the Ethiopian case highlights important lessons for South Africa, with its high unemployment rate coupled with

a small informal sector. This unique situation requires a lot more focus in the development of incentives that will attract and

retain female entrants into self-employment as a potential solution to this labour market characterisation. From Ethiopia, it is

important to learn the importance of exhaustively identifying the barriers faced by female entrants and setting out to develop

cost-effective solutions.

Where funds are provided, it is important to ensure that the level of funding is sufficient for the business needs and the

broader growth objectives envisioned by the programme or the scheme. This is key to the overall sustainability of the financing

institution and the recipient firm. In the case of Ethiopia, while there has been some progress, for some schemes, such as the

export trade duty incentive scheme, it has been argued that the government has not adequately evaluated the cost and gains

of the subsidy (Regassa, 2008).

4.1.4. germany

Germany, Europe’s most industrialised and populous country, is a federal parliamentary republic around 30 percent the

geographical size of South Africa. As levels of unemployment and vulnerable employment are low for both male and female

workers, efforts to support women in the German economy focus on increasing women’s influence in the economy through

ensuring career progression and broadening ownership. We consider several initiatives supported by the German government

toward this aim.


Much of the support for women in Germany is directed by the National Agency for Women Start-up Activities and Services

(“Bundesweite Grunderinnenagentur” or “bga”), established in 2004. The agency promotes and directs women entrepreneurs

to national and state-level support programmes (OECD, 2015). It is funded by the following three federal ministries: Education

and Research; Economic Affairs and Energy; and Families, Senior Citizens, Women and Youth. Each of these line ministries cover

specific programmes and initiatives which are then overseen by the bga head office. Co-funding at the regional level is also

provided by the European Social Fund.

The bga is active at all levels of government. Its national responsibilities include information collection and dissemination and,

advisory services. Regional office responsibilities include development and coordination of support programmes and linking

regional activities to national actions. bga also works with a range of 2 000 local partners to provide a wide range of activities,

services and initiatives, namely business counselling, entrepreneurship training, coaching and mentoring, networking support,

facilitating access to finance, and political lobbying (OECD, 2015).



box iv. The bga’s Purpose and mission

The bga’s purpose and mission is to encourage women to become entrepreneurs by:

Offering female-specific support services at all stages of business development;

Developing women’s entrepreneurship networks;

Promoting women’s entrepreneurship role models; and

Promoting an entrepreneurial culture among women and society, more generally.

The bga “bundles programmes, information and services regarding female entrepreneurship provided by different initiatives

at the state or federal levels”. It targets potential female entrepreneurs and provides support across all industry sectors and

at all phases of business development. It also supports research and promotes women’s entrepreneurship in the media.Source: OECD. (2015). Supporting Women Entrepreneurs in Germany. OECD- European Commission.

Presently, the bga’s focus is on advancing the nexxt Initiative. This is a joint initiative of the Federal Ministry for Economic

Affairs and Energy, KfW Bank Group and representatives of various institutions and organisations. It aims to create a favourable

climate for the newer and younger German entrepreneurs.13 The programme aims to support younger entrepreneurs to

take over established businesses, and in so doing increase their participation as owners in the economy while ensuring that

existing businesses continue successfully in the future through the new owners. While this is not an initiative directly aimed at

women, female entrepreneurs are made aware of and encouraged to participate in the initiative through the bga. The agency

thus serves to promote broader government initiatives to women and increase their participation therein.


We have noted a significant volume of support for women entrepreneurs through the bga agency. However, the involvement

of this agency, particularly with respect to access to finance, was simply to direct women to relevant initiatives and programmes.

The OECD notes this shortcoming and references the observation of Dehoff-Zoch (2012) that although women account

for one in three individuals seeking financial products, the needs of women have not been met by mainstream financing

products. Most start-up financing programmes do not target any specific group. Therefore, women typically access finance

through the mainstream offerings at national and state level. We consider the most important of these below.

Kreditanstalt für Wiederaufbau (KfW) is the third largest bank in Germany responsible for designing national programmes

and subsidies on behalf of federal ministries. It offers several financial products for new and existing business owners in

conjunction with the Federal Ministry for Economic Affairs and Energy. In addition to the national offerings through KfW, states

are also active in facilitating access to finance for entrepreneurs. For example, NRW.Bank is a public subsidiary bank in North

Rhine Westphalia, owned by the state government with a mandate to foster business start-ups and ownership in the region.

Finally, government-supported finance may be accessed through the microcredit sector. Support here can be found in two

forms: through the broader microcredit sector which is supported by a national fund (Mikrokreditfonds Deutschland); and

through a dedicated Micro-mezzanine fund (Mikromezzaninfonds Deutschland) which aims to increase the range of financing

opportunities for very small businesses and new start-ups.

Microcredit is currently granted by microfinance institutions that are accredited by the German Microfinance Institute e.V.

(Deutsches Mikrofinanzinstitut, DMI). A number of these microfinance institutions are dedicated to supporting women

entrepreneurs. One such example is the association Goldrausch, which provides microcredit to self-employed women and

female business owners seeking to expand their business.

13 http://www.existenzgruenderinnen.de/DE/Unternehmensnachfolge/nexxt-Initiative/nexxt-initiative_node.html


The Micro-mezzanine Fund (Mikromezzaninfonds Deutschland) was launched by the Federal Ministry for Economic Affairs and

Energy in 2013 to provide additional financing opportunities for small businesses and new start-ups. The fund was launched

with EUR 35 million and has since been increased to EUR 85 million in 2015. The Fund provides qualifying businesses with

equity of up to EUR 50 000. This improves the companies’ credit rating and increases their chances of securing further finance.

The Fund offers financing for up to 10 years at a fixed rate of 8 percent per annum and with a profit-sharing component of 1.5

percent per annum. The Fund is open to all individuals seeking to start a business, with a specific focus on female and migrant

applicants (OECD, 2015).

4.1.4.3. Summary

The German approach to increasing women’s participation in the economy appears focused on increasing their visibility and

ownership in the economy rather than merely empowering broader access to economic participation. This contrasts with a

country such as South Africa, where considerable challenges remain with respect to women being able to access decent work

and business opportunities in the economy and measures to support women in the country must be mindful of this context

to address the most pressing challenges facing women in the country.

A further lesson for South Africa may be taken from the German approach to proffering support to women that involves

a well-coordinated policy strategy requiring collaboration across different government departments, levels of government

and relevant external organisations. Such a coordinated approach may be useful in the South African context given the

various interlinked challenges to women’s full participation in the economy that fall within the mandates of a number of

different ministries. Importantly, it may serve as a powerful mechanism to bring on board both the private sector and non-

governmental organisations operating in this area, thereby promoting synergies between the various available programmes

and interventions.

4.1.5. Thailand

Thailand is a constitutional monarchy and a member of the Association of South East Asian Nations (ASEAN). Over the last four decades, the country has made significant development strides shifting from low value-added sectors of production to the current high value-added ones (OECD, 2015). Despite this transformation, however, one in two employed individuals works in the informal sector, often as unpaid family labour, or in the agricultural sector (World Bank, 2017). Furthermore, women face vertical gender segregation as they tend to occupy lower-skilled occupations often in sectors that pay lower wages. This is the case despite the increase in the share of women transitioning from the agricultural sector to the retail trade and manufacturing sectors. Women are slightly more likely than men to work as self-employed or unpaid family labour, with 55 percent of female employment falling into this category (compared to 50 percent of male employment) (World Bank, 2017). There are a limited number of labour market incentive policies specifically targeted at women. This is likely due to the overall low unemployment levels and the fact that Thailand ranks relatively highly in terms of the representation of women in business (Grant Thornton, 2014).


Direct government support for women is coordinated by the Office of Women’s Affairs and Family Development (OWAFD) established in 2002 under the Ministry of Social Development and Human Security. OWAFD partners with donor organisations to promote women’s economic empowerment and serves as the implementing agency for the promotion of gender equality in the country. The Office implements policies, measures and mechanisms to support other public and private sector units in their own policy implementation promoting women’s economic potential, their rights, and gender equality and equity (OWAFD, 2018).

Support for female entrepreneurs is additionally offered through the Women’s SME Association of Thailand which was established in 2007 to promote access to markets for female entrepreneurs while simultaneously promoting the strength of women networks. Another initiative aimed at strengthening the network of Thai female entrepreneurs is the Women’s



Enterprise Incubation Centre, which provides advice to women entrepreneurs, organises activities to promote motivation and innovation, seeks to develop the body of knowledge on business, and offers an e-learning kit to promote capacity building for women in their careers along with access to information and rights. Further, the Business and Professional Women’s association of Thailand (BPW Thailand) is another organisation focused on developing the capabilities of women in the Thai economy.

The launch of the ASEAN Women’s Entrepreneurship Network (AWEN) in 2014 represents another platform though which Thai women can access additional support. This network serves as a platform for the “promotion, development and empowerment of women entrepreneurs in the ASEAN region by addressing the challenges they face in finance, networking and training” (OECD, 2017). In Thailand, AWEN’s objectives are overseen by OWAFD.


As noted above, overall, there is a limited number of direct incentive programmes run by the Thai government aimed at either employment creation, skills building, advancing the transition of unpaid family labour to paid labour or the promotion of leadership and participation skills for women. However, women stand to benefit from the numerous avenues of support afforded to SMEs in the country as they form a large proportion of the self-employed and informal entrepreneurs.

Chief among these initiatives is the SME Promotion Office, a semi-autonomous governmental agency whose responsibilities include, among others, coordinating the formulation of an SME Promotion Action Plan, preparing the SME Status Report, managing an SME Promotion Fund and acting as the Secretariat to the SME Promotion Committee.14 The office is authorised to invest in and provide financial support to SME promotion agencies. While the SME Promotion Office does not have an overt gender mandate it reinforces the central role of SMEs for their employment generation capacity (Turner et al, 2016).15

Assistance is available to SMEs through the ASEAN association which offers support to eligible enterprises operating in rural and agriculture-based communities. The ASEAN SME Agencies Working Group (SMEWG), which includes representatives from all ASEAN SME agencies, exists to formulate policies and programmes and to implement initiatives for SME development and cooperation across the region.

Of the strategic goals contemplated under the SME Master Plan16, facilitating access to finance is one of the most important, particularly for women. The increase in the number of microfinance institutions followed a government mandate implemented in conjunction with the Asian Development Bank to increase financial inclusion and access to finance for lower income, and particularly rural households (Bird, Hattel and Sasaki, 2011). The microfinance policy of the Thai government has been successful in reducing credit constraints for female entrepreneurs. Microfinance funds, and Thailand’s “village funds”—which boasted a loan portfolio of $4.9 billion in 2011—create pathways for female-headed households to gain access to credit and finance enabling entrepreneurship. In addition, the regulation governing how fund committees in villages are managed stipulates that a similar ratio of female and males must be present, again empowering women in these communities (de la Huerta, 2010).

Additionally, Thailand’s SME Development Bank provides financial and non-financial support to advance the government policy of promoting SMEs. The Bank offers a range of products to assist entrepreneurs in meeting their funding requirements. These include credit guarantees and loans for business expansion or improvement. Though not specifically targeted at women,

it is estimated that approximately 50 percent of the SME Bank’s recipients of finance are women.17

14 Source: http://www.sme.go.th/en/page.php?modulekey=73 (Last Accessed: 31 January 2018).

15 The currently operational Fourth SME Master Plan relates to the period 2017 to 2021. The plan sets a target for SMEs to contribute to 50 percent of total GDP in the country and focuses on creating an enabling business environment that develops the capacity of SMEs to effectively run their business operations in a manner that applies knowledge, creativity and innovation.” This will be achieved through the following specific activities: enhancing productivity, technology and innovation; promoting capital access; promoting market access; developing and promoting entrepreneurship; developing tools for efficient implementation; revising regulations and laws to support SMEs; promoting SME clusters; and strengthening fundamental enterprise. Source: http://aec.utcc.ac.th/wp-content/uploads/2017/11/2016-11-Role-of-OSMEP-Thailand-4.0.pdf (Last Accessed: 31 January 2018).

16 Source: Small and Medium Enterprises (SMEs) in ASEAN. Available: http://www.aseansme.org/aboutus.

17 Loans through the SME Development Bank of Thailand (SME Bank). Available: http://www.we-apec.com/directory/loans-through-sme-development-bank-thailand-sme-bank and Small and Medium Enterprise Development Bank of Thailand. Available: https://www.smebank.co.th/. Last Accessed: 31 January,2018


Here, it should be emphasised that a challenge that arises in many Asian countries such as Thailand is the prevalence of

informal enterprises that employ a significant proportion of women. Regarding government support, the implication of

informality is often that such women-led businesses are often excluded from assistance as they lack registration documents

or other criteria necessary to access aid. USAID (2013) notes that women in these countries have indicated that formalising

their businesses was a long and time-consuming process. They are thus reluctant or unable to do so which further limits their

ability access to support initiatives and eventually, their long-term growth.

Finally, women may benefit from incentives and initiatives of Thailand’s Board of Investment (BOI). Through the Board’s

Investment Promotion Act and Competitive Enhancement Act, a range of tax incentives and benefits are offered to businesses

across a range of sectors, including agriculture, mining, electronics, services and public utilities. While these incentives are not

directly gender-focused, they may stand to benefit firms that have a high percentage of female employees as well as Thailand’s

growing number of female entrepreneurs. The incentives are available for higher skilled industries and includes exemptions

on the following: import duties on imported machinery, raw and essential materials imported for manufacturing processes.

Tax-based incentives are also on offer to firms that invest in R&D, train in advanced technology, develop local supply chains

and choose to have their international or regional operating headquarters based in Thailand (PWC, 2018).

4.1.5.3. Summary

The structure of the Thai economy contrasts to the South African economy. First, while South Africa faces high unemployment

(persistently over 24 percent over the past five years), the Thai unemployment rate is remarkably low (1.4 percent). This low

unemployment rate can be explained by the existence of a large informal sector and the relative importance of agricultural

self-employment in Thailand. The large informal sector, however, represents a challenge regarding the type of support and

development for entrepreneurs, particularly women entrepreneurs. Regional- and country-level SME strategies point towards

easing the formalisation process for participants in the informal sector so that they can access relevant support initiatives.

While South Africa does not have a similarly large informal sector, it has a large pool of unemployed who too could benefit

from accessing entrepreneurship support. The Thai experience suggests that not only should these unemployed be supported

to become economically active; but that efforts should be made to ensure they are able to access initiatives intended for their

empowerment. This may mean supporting the facilitation of the process of enterprise formalisation, where appropriate, in

South Africa, and not just looking to increase inclusion in the economy.

A further lesson that to be adopted from the Thai experience is the value of collaboration between different countries in order

to learn from what worked and avoid what failed. This is illustrated in Thailand in two ways: through AWEN the association of

Women’s Entrepreneurship that allows for information sharing through the platform and through SMEWG which facilitates

a channel for policy to be formulated and for input to be given to current policies. Similarly, South Africa can identify the

appropriate forum, although SADC seems a logical choice in that most, if not all countries in the region face significant

challenges with respect to formality, entrepreneurship and gender equity.

4.2 The dti’s incentive Programmes

4.2.1. The dti’s approach to incentives

The dti’s objectives include the facilitation of broad-based economic transformation and the encouragement of industrial

development, competitiveness and trade integration, amongst others. In order to achieve these objectives, the dti has

implemented various support programmes. The DTI division that provides fiscal and non-fiscal support to various economic

activities is the Incentive Development and Administration Division (IDAD), which administers and manages the incentives

schemes. The purpose of IDAD is to stimulate and facilitate the development of enterprises through the effective and accessible

incentive projects that support national priorities (DTI, 2015). The division achieves this through the design, administration,

clustering, monitoring and evaluation (M&E) of a wide spectrum of incentives for micro to large enterprises (DTI, 2015).



The IDAD has grouped the incentive programmes into five clusters. These are:

i. Broadening Participation, which encourages broader participation for historically disadvantaged individuals into the

mainstream economy;

ii. Competitiveness Investment, which promotes industrial competitiveness;

iii. Manufacturing Investment, which stimulates additional investment in the manufacturing sector;

iv. Services Investment, which encourages greater investment and growth in the services sector; and

v. Infrastructure Investment Support, which leverages investment through infrastructure development (DTI, 2015).

South Africa’s persistently high unemployment rate remains a key challenge faced by a significant number of people; this is

particularly true for for women and the youth (DPRU, 2016). In 2018Q2, the expanded unemployment rate for women was 39.1

percent compared with 32.3 percent for men; amongst youth aged 15 to 24 years, the expanded unemployment rate was 67.1

percent, nearly twice the national average. Government has introduced various policies and programmes that aim to address

unemployment, either directly or indirectly. One of these programmes is the IDAD.

The budget allocation for IDAD has varied over the years across different incentives clusters. Figure 10 presents the budget

allocations for each cluster for the period 2012/13 to 2016/17. The Manufacturing Incentives Cluster (MIC) accounted for the

largest budget allocation over the reported period, followed by the Infrastructure Investment Support and Services Investment

Incentives. In 2016/17, nearly two-thirds (63.3 percent) of the IDAD budget was allocated towards the MIC; this is more than

2.5 times the share allocated for the Infrastructure Investment Support Cluster (24.1 percent) and more than five times the

budget allocation for the Services Investment Incentives Cluster (11.8 percent). Just 0.9 percent of the budget went towards

the Broadening Participation Incentives Cluster, the PSDC, and the Strategic Partnership and Customer Care combined.

figure 10. iDaD incentives budget, 2012/13-2016/17

0

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Cluster

Source: National Treasury (various years)

Notes: 1. Data on IDAD programmes expenditure is categorised under these six clusters. 2. Budget allocation is for operational and capital expenditure.


IDAD offers incentives through grants, loans, and tax allowances. The value of grants, tax allowance and loans was R12.8

billion during the 2016/17 financial period (DTI, 2017). A large share of incentives is in the form of cost-sharing grants and tax

allowances (Figure 11). In 2016/17, close to half the IDAD incentives budget was allocated through grants (48.9 percent), 7.5

percentage points higher than during the previous financial year. Tax allowances fell from R6.2 billion in 2015/16 to R4 billion in

2016/17, a decline of 35.5 percent. A relatively small proportion of the incentives are provided through loans: in 2015/16, only

R23.7 million of the incentive was allocated through loans (0.2 percent of the total), but the loan facility increased substantially

to R871.1 million in 2016/17 (6.8 percent). This may indicate that access to finance has improved for entities which are not

eligible for grants or tax allowances. Lastly, the Special Economic Zones (SEZ) are economic zones in specific sectors to promote

economic development. In 2016/17, SEZs accounted for 13.2 percent of the IDAD incentive budget.

figure 11. iDaD incentive structure, 2015/16 and 2016/17

41.4

0.2

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48.9

6.8

13.2

31.1

2015/16 Financial Year 2016/17 Financial Year

GrantsLoansSEZTax Allowance

Incentive Type

Source: IDAD Incentives Report (2016/17)

The IDAD offers financial support to stimulate and facilitate economic development and it is of interest to look at how many

projects were given support.18 Figure 12 shows the number of projects approved and the value of the projects since 2013. In

2013, 3 989 projects to the value of R7.7 billion were approved.19 By 2016, the number of approved projects had fallen by more

than half to 1 549, while their value was two-thirds higher at R12.8 billion. This shift suggests that there has been something

of a structural shift in the composition of approvals, from more projects with a smaller average value to fewer projects with a

larger average value. It is not clear whether this shift is the result of a policy change shifting focus to larger value projects, or

whether it is the result of changes in the pool of applicants. Certainly, this is an interesting change, given the emphasis within

the broader policy debate on the importance of small, medium and micro-enterprises (SMME) in terms of shared growth and

job creation. However, without evidence on the impacts of dti programmes across the full range of firms, it is not possible to

determine whether or not this change in emphasis is a rational response to differing outcomes across firm size. This question

points to the value of appropriate evaluations of interventions as a tool for guiding policy.

18 “Project” means the business operated by the Beneficiary and that was approved for the incentive. https://eip.thedti.gov.za/DTI/Default.aspx

19 Unless otherwise stated, all rand values are in nominal terms.



figure 12. iDaD overview, 2012/13 to 2016/17

3989

3384

4137

1962

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Source: IDAD Incentives Report (2013, 2014, 2015, 2016, 2017)

figure 13. iDaD approvals, by number and value, 2016/17

Number of approvals

Projected investment

0.0

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Mean Project Value

Source: IDAD Incentives Report (2016/17).

During the 2016/17 financial year, three provinces—Gauteng, KwaZulu-Natal and the Western Cape—accounted for the

lion’s share of approvals and approved value: (Figure 13). These three provinces include the five largest of South Africa’s

eight metropolitan municipalities, which are home to large populations and generate a disproportionately large share of

total economic output. These three provinces accounted for approximately nine out of ten (88.8 percent) approved projects.

Gauteng accounted for the highest share of approved projects (38.5 percent), followed by the Western Cape (35.9 percent) and

KwaZulu-Natal (14.4 percent). In terms of total project value, KwaZulu-Natal had the highest value (36.0 percent), followed by


Gauteng (30.5 percent) and the Western Cape and Eastern Cape both accounted for 11.7 percent. These differences suggest a

differing mix of projects in each province, with projects in Free State being relatively high value on average, while those in the

Western Cape were of relatively low value on average.

To what extent are these approved projects associated with investment and job creation? Figure 14 presents the projected

investment ratio and projected incentive cost per new job for 2016/17 across province. The projected investment ratio is

defined as the ratio between the total estimated value of the additional investment leveraged through IDAD incentives and

the total value of these incentives. A higher ratio indicates that the incentives are expected to leverage a relatively larger

amount of investment. On this metric, the Northern Cape performs particularly well, with each R1 of IDAD incentives linked

to R6.80 in additional investment. The Northern Cape is followed by the Free State and Limpopo (both at a ratio of 4.2:1). In

contrast, the ratio in Mpumalanga is just 0.4:1, meaning that each R1 of IDAD incentives is linked to additional investment of

R0.40.

figure 14. Projected investment ratio and projected incentive cost per new job, 2016/17

3.1

0.2

1.9 1.9

6.8

0.3

4.2

1.2

3.4

1.0

3.1

1.2

2.8

0.5 0.4

4.2

2.4

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

Ratio

/ R m

illion

Western Cape

Eastern Cape

Northern Cape

Free State

KwaZulu-Natal

North West

Gauteng

Mpumalanga

Limpopo

Projected investment ratioIncentive cost per projected job


Notes: 1. The projected investment ratio is the ratio between the total estimated value of the additional investment leveraged by IDAD incentives, and the total value of the IDAD incentives. 2. The projected incentive cost per new job is calculated as the total value of IDAD incentives divided by the number of new jobs projected to be created due to the IDAD incentives. 3. There were zero projected jobs in Mpumalanga in this financial period.

The projected incentive cost per new job relates the projected number of new jobs to the value of incentives provided by

IDAD. A higher value indicates a higher cost per new job. On this metric, the Northern Cape once again ranks highly with a

cost of R0.3 million per projected new job. The only province where this cost is lower is the Western Cape (R0.2 million per

projected new job), while in Gauteng the cost is R0.5 million per projected new job. The two provinces with the highest cost

per projected new job are Limpopo (R2.4 million) and the Eastern Cape (R1.9 million).

In summary, IDAD provides financial assistance through grants, loans and tax allowances to emerging or expanding enterprises

to promote economic development. A large proportion of incentives are in the form of cost-sharing grants and tax allowances.

The vast majority of approved projects were located in Gauteng, KwaZulu-Natal and the Western Cape. Similarly, these three

provinces forecasts the highest share of investment compared to other provinces. However, the Western Cape is creating jobs

at the lower cost compared to Gauteng and KwaZulu-Natal in particular.



4.2.2. overview of the dti incentive schemes

4.2.2.1. Broadening Participation Cluster

The Broadening Participation cluster is designed to broaden economic participation of small enterprises owned by historically

disadvantaged communities and marginalised regions (DTI, 2016/17). This cluster consists of three schemes, each targeting

different enterprises, namely: (i) the Black Industrialist Scheme (BIS), (ii) the Technology and Human Resources for Industry

Programme (THRIP), and (iii) the Support Programme for Industrial Innovation (SPII). In total, the BPS approved 65 projects

to the value of R1.2 billion during the 2016/17 financial year. This cluster is projected to attract R3.4 billion in investment and

create 3 979 new jobs (Table 17). The total disbursed amount was R144.9 million in the 2016/17 period; the BPS therefore

accounted for 3.2 percent of the total IDAD incentives budget.

Table 17. The broadening Participation Cluster, 2016/17

scheme

Proj

ects

ap

prov

ed

ince

ntiv

e va

lue

(R m

il)

Proj

ecte

d in

vest

men

t (R

mil)

Proj

ecte

d ne

w jo

bs

base

line

jobs

Dis

burs

ed

(R m

il)

stud

ents

to

be

sup-

port

ed

Dis

burs

ed/

valu

e ra

tio

BIS 36 1 000.0 3 100.0 3 979 3 837 122.5 n.a. 0.12

THRIP 23 158.2 251.0 n.a. n.a. 1.6 75 0.01

SPII 6 13.4 14.3 20.8 n.a. 1.55

Share of IDAD (%) 4.2 9.2 8.5 3.2


Notes: 1. Blank fields are due to data unavailability.

In summary, the BPS has protected 10.0 percent of the total IDAD baseline jobs. This cluster accounts for only 4.2 percent of

total IDAD approved projects; however, it is linked to R3.5 billion in investment and the creation of a projected 3 979 jobs.

black industrialist scheme (bis)

The BIS came into effect from February 2016 with the aim to promote industrialisation, sustainable economic growth and

transformation through the support of black-owned entities in the manufacturing sector. Subsectors of particular focus are oil

and gas, agro-processing, nuclear energy and the blue ocean economy (DTI, 2016/17). The qualifying criteria for this scheme is

that enterprises start a new operation or expand, upgrade or acquire an existing business or operation (DTI, n.d.).20

In 2016/17, the BIS accounted for more than half (55.4 percent) of the approved projects from the Broadening Participation

cluster and 85.4 percent of the cluster’s budget. In the same period, this scheme is estimated to have attracted R3.1 billion in

investment and created 3 979 new jobs. Moreover, this scheme has protected 3 837 baseline jobs.

Technology and Human Resources for industry Programme (THRiP)

THRIP was introduced in 1991 as a result of the shortage of high-level skills for industry seen at the time (THRIP, 2016). The main

objective of this scheme is to leverage collaborative partnerships on a cost-sharing basis to produce highly skilled human

resources and technology solutions in order to improve industry competitiveness through partnership between government,

industry and academia (DTI, 2016/17). In 2016/17, 23 projects with the value of R158.2 million were approved, with a total

investment of R251 million. The programme has supported 75 students during this period, with a total disbursement of R1.6

million; on average, therefore, each student received financial support of R21 333 during this period.

20 http://www.dti.gov.za/financial_assistance/financial_assistance.jsp


THRIP has made progress in meeting its objective of producing high-level education and skills training. On average, THRIP

led to 50 patents (local and international) and 1 823 research articles, and supported 1 607 postgraduate students annually

(DPME, 2015). Of these students, more than half were Master’s degree students (53.8 percent), while just over one-quarter

(27.7 percent) were doctoral students, with the remaining 18.5 percent being honours students (18.5 percent). Unfortunately,

information related to the gender of beneficiaries was not located.

Figure 15 compares the variation of THRIP outcomes over time from the base year of 2002. The rise of doctoral students has

increased more rapidly compared to their counterparts. The THRIP support towards doctoral, masters and honours students

has followed an upward trend since 2002. In 2013, the THRIP support towards doctoral students increased substantially by 167

percent from the base year of 2002. In contrast, the THRIP led patents decreased markedly by 31 percent from the base year.

This means that THRIP has increased support to postgraduate students and support towards patents and research articles has

been shrinking over time.

figure 15. THRiP outcomes, 2002-2013

0

100

200

300

400

500

Index

(200

2=10

0)

2001/02 2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11 2011/12 2012/13

Patents (local & international)Research articlesHonours degree graduateesMasters degree graduatesDoctoral degree graduates

Outcome

Source: DPME (2015)

Notes: All series are indexed so that 2002=100.

support Programme for industrial innovation (sPii)

The SPII scheme objective is to encourage technology development by providing financial assistance for innovative products

or processes that are commercially viable and internationally competitive (DTI, 2016/17). This scheme was transferred to the

DTI in February 2015, having initially been administered by the Industrial Development Corporation (IDC). In 2016/17, six

projects to the value of R13.4 million were approved, with R14.3 million projected investment.

4.2.2.2. Manufacturing Investment Cluster

The Manufacturing Investment Cluster (MIC) aims to address market failures and economic shortfalls as well as to promote

and stimulate the manufacturing sector production (DTI, 2016). This cluster consists of five schemes each targeting different

enterprises, namely: the 12I Tax Allowance Incentive (12I); the Automotive Incentive Scheme (AIS); the Manufacturing

Investment Programme (MIP); the Aquaculture Development Incentive Programme (ADEP); and the Incubation Support



Programme (ISP). In total, the MIC approved 631 projects to the value of R8.1 billion during the 2016/17 financial year. This

cluster is projected to attract R30 billion in investment and create 3 975 new jobs (Table 18). The total disbursed amount is R2.5

billion in the 2016/17 financial period; this represents more than half (53.4 percent) of the total IDAD incentives disbursement.

This is approximately seven times the disbursement to the Broadening Participation Cluster. This cluster is particularly important

in retaining employment as nearly 35 000 jobs of total IDAD baseline jobs are supported under this cluster.

Table 18. manufacturing investment Cluster, 2016/17

scheme

Proj

ects

ap

prov

ed

ince

ntiv

e va

lue

(R m

il)

aver

age

proj

ect

valu

e (R

m

il)

Proj

ecte

d in

vest

men

t (R

mil)

Proj

ecte

d ne

w jo

bs

base

line

jobs

new

jobs

su

ppor

ted

Dis

burs

ed(R

mil)

12I 25 3 983.4 159.34 14 300 1 148 3 983.4

AIS 88 3 600 40.9 12 400 2 370 34 788 2 000

MIP 5081 400.8 0.79 26 030 400.8

ADEP 8 45 5.63 198 220 141 20

ISP 2 27.7 13.85 55.5 237 34.5

Share of IDAD (%) 40.7 20.4 12.8 53.42


Notes: 1. Refers to the number of claims in 2016/17. 2. Share excludes tax allowance. 3. Blank fields are due to data unavailability.

12i Tax allowance incentive (12i)

The 12I scheme was introduced in July 2010 with the objective of encouraging industrial upgrading and use of new technology

in manufacturing (DTI, 2016). This incentive is the only scheme that provides tax allowances. The qualification criteria for this

scheme is a minimum investment in qualifying assets of R50 million for new projects, or additional investment in qualifying

assets of R30 million for expansion or upgrade on current projects.

In 2016/17, 25 projects were approved to be exempted from paying R4 billion in taxes. This scheme projects investment of

R14.3 billion and the creation of 1 148 new jobs. On average, each project was exempted from paying R159.3 million worth of

taxes. The 12I budget was committed on investment to the value of R3.9 billion and training to the value of R83.4 million. This

scheme accounts for 4.9 percent of total IDAD estimated job creation, although at a higher cost compared to other schemes.

automotive incentive scheme (ais)

The Automotive Incentive scheme is designed to provide support for capital investment and training for greenfield and

brownfield investments (DTI, n.d.). Greenfield investments refer to new industrial projects that use new and unused

manufacturing assets, while brownfield investment refer to the upgrading or expansion of existing industrial projects (DTI,

n.d.). The AIS aims to assist firms or projects within the automotive sector to enhance plant production, retain employment

and strengthen the automotive value chain (DTI, 2017). This scheme comprises of five subcomponents, namely: component

manufacturers (CM); original equipment manufacturers (OEM); people-carrier automotive investment scheme (P-AIS); medium

and heavy commercial vehicles (MHCV); and medium and heavy component manufacturers (MHCM) (DTI, 2017).

The incentive has expanded since its inception in July 2009. The scheme initially provided support to CM and OEM manufactures,

then added the P-AIS in 2014 and finally supported the MHCV and MHCM in 2014 (DTI, 2015). In 2016/17, 88 projects to the

value of R3.6 billion were approved. On average, each project was valued at R40.9 million. This scheme projects investment of

R12.4 billion and 2 370 new jobs, twice the projected new jobs from 12I. Moreover, the AIS secures 34 788 jobs.


manufacturing investment Programme (miP)

The MIP is a reimbursable cash grant designed to support foreign- and local-owned textile and clothing manufacturers who

intend to start-up a production facility, or to expand or upgrade the existing production facility (DTI, n.d.). The MIP scheme

was introduced in May 2008 with the aim of encouraging investment and economic growth by providing financial support to

small and medium-to-large sized enterprises within the manufacturing sector (DTI, 2015).

In 2016/17, 508 claims were made with a total value of R400.8 million. On average, each claim was valued at less than a million

(R788 976). The MIP has supported 26 030 new jobs, accounting for 1.5 percent of national manufacturing sector employment

(1.7 million) in 2016.

aquaculture Development incentive Programme (aDeP)

The ADEP is a reimbursement cost-sharing grant designed to support South African registered enterprises involved in primary,

secondary and ancillary aquaculture activities (DTI, n.d.). The grant amounts to a maximum of R30 million for qualifying capital

costs, which goes directly to approved projects wishing to start-up or expand or upgrade (DTI, n.d.). The ADEP scheme was

launched in March 2013 targeting specific sectors in the primary, secondary and ancillary aquaculture activities with the aim

to enhance aquaculture sector investment, thereby stimulating production, sustaining and creating jobs, across different

locations, and to widen participation (DTI, 2015).

In 2016/17, eight projects were approved to the value of R45 million, with an average value of R5.6 million. This scheme

projects a R198 million investment and 220 new jobs. In addition, there were short-run positive employment outcomes during

this period, with 141 new jobs supported within this scheme. However, the actual disbursement was only R20 million, less

than half the incentives value.

incubation support Programme (isP)

The ISP was designed to grow incubators and create effective enterprises with the potential to develop communities and

support local and national economies (DTI, n.d.). This incentive scheme intends to align SMMEs into the mainstream economy

through the support provided by the incubators in order to strengthen economic development through broadening

participation in the economy (DTI, n.d.). The ISP was launched in October 2012 to facilitate partnerships between small and

big businesses with the intention of big businesses transferring to SMMEs skills related to enterprise development, supplier

development and marketing (DTI, 2015). However, during November 2016 the ISP was halted and was replaced by the

Strategic Partnership Programme (SPP), with the aim of enhancing supplier development and inclusion of new suppliers into

the value chain (DTI, 2016).

In 2016/17, two projects were approved with a combined value of R27.2 million. On average, each project was valued at

R13.9 million, slightly higher than the average project size of this cluster (R12.8 million). This scheme projects investment of

R55.5 million and 237 new jobs during this period. The amount disbursed is R34.5 million, this is R6.2 million higher than the

approved incentive value.

4.2.2.3. Services Investment Cluster

The Services Investment Cluster (SIC) is a collection of the dti’s incentive programmes that aim to support businesses operating

in the services sector (DTI, 2015). This cluster currently consists of two schemes each targeting different components of the

services sector, namely: Business Process Services (BPS); and Film and Television Production (Film and TV). In total, the SIC

approved 107 projects between the two incentive programmes, together amounting to an incentive value of R870.8 million

(Table 19). The Film and TV incentive accounted for most of this expenditure with 90 percent of total projects approved and

94 percent of the total incentive value in the cluster. In terms of the entire IDAD, the SIC makes up 6.9 percent of total projects

approved, 6.8 percent of the total incentive value of all five clusters and accounts for 17.4 percent of total disbursed funds.



Table 19. services investment Cluster, 2016/17

scheme Projects approved

incentive value(R mil)

average proj-ect value

(R mil)


(R mil)

Projected new jobs

Disbursed

(R mil)

BPS 11 52.2 4.7 6 687 288

Film & TV 96 818.4 8.5 3 800 6 029 513

Share of IDAD (%) 6.9 6.8 8.2 54.5 17.4


Notes: Blank fields are due to data unavailability.

business Process services (bPs)

The Business Process Services (BPS) incentive was first introduced in 2011 with the objective of creating employment

opportunities for the South African youth and to contribute to South Africa’s export revenue by offering a suite of offshoring

services (DTI, 2015). After a revision in 2014, the programme now consists of two components. The first is a base incentive

that offers a five-year operational expenditure (OPEX) grant to create and maintain complex and non-complex jobs (i.e.

remuneration of greater than R300 000 per year). The second component consists of a bonus incentive for non-complex

jobs, which is offered to applicants that are able to create and maintain 400 or more offshore jobs over a five year period. The

scheme is designed to support start-up operations or the expansion of existing operations.

Across the 11 programmes approved and the R288 million disbursed thus far to the BPS incentive, 6 687 new jobs have been

projected (Table 19). In terms of women’s economic empowerment, Figure 16 disaggregates the jobs supported by the BPS

between 2013/14 and 2016/2017 by gender. The first thing that stands out is that the number of female jobs supported

exceeds the number of male jobs supported in the BPS sector. The number of female jobs supported rose from 14 751 in

2013/14 to a peak of 32 875 in 2015/16, before falling somewhat to 26 400 supported jobs in 2016/17. The number of male

jobs supported rose from 11 254 in 2013/14 to 18 497 jobs in 2016/17.

figure 16. bPs jobs supported, 2013/14-2016/17

11254

14751 15015

21210

5114

32875

18497

26400

0

5000

10000

15000

20000

25000

30000

35000

Jobs

supp

orted

2013/14 2014/15 2015/16 2016/17

MalesFemales

Gender

Source: IDAD Incentive Report (various years)


The BPS has supported 44 897 of the total IDAD jobs, of which women account for close to three-fifths. The share of projects

approved under this scheme was only 0.7 percent of total IDAD approved projects, but accounts for an estimated R7.1 billion

in export revenue in 2017.

film and Television Production (film and Tv)

The second incentive programme in the Services Investment Cluster is the Film and Television Production and Post-production

(Film and TV) incentive. It is divided into three sub-programmes consisting of the Foreign Film and Television Production and

Post-production (Foreign Film and TV) incentive; the South African Film and Television Production and Co-production (SA

Film and TV) incentive; and the South African Emerging Black Filmmakers (EBFM) incentive. The shared objectives for all three

sub-programmes are to create jobs, to increase the country’s technical skills base and to increase investment through the

qualifying South African production expenditure (QSAPE) spent within South Africa. The job creation forecast for this incentive

programme is 6 029 new jobs in the 2016/17 year.

4.2.2.4. Competitiveness Investment Cluster

The Competitiveness Investment Cluster (CIC) is designed to promote structural transformation in the economy and to create

a dynamic industrial and globally competitive South Africa (DTI, 2014). This cluster consists of four schemes each targeting

different enterprises, namely: the Manufacturing Competitiveness Enhancement Programme (MCEP); the Export Marketing

and Investment Assistance (EMIA); the Sector-Specific Assistance Programme (SSAS); and the Capital Projects Feasibility

Programme (CPFP). In total, the CIC has approved 842 projects to date with a combined incentive value of R1.1 billion (Table

20). The CIC has also disbursed R1.1 billion to date across all four incentive schemes. Projects approved for the CIC makes up

54.4 percent of all IDAD-approved projects, as well as 8.8 percent of the value of all IDAD incentives 23.5 percent of total IDAD

disbursements.

Table 20. Competitiveness investment Cluster, 2016/17

scheme Projects approved incentive value(R million)

average project value(R million)

Disbursed(R million)

MCEP 377 989.2 2.6 989.2

EMIA 408 32.1 0.1 22.3

SSAS 521 74.3 1.4 51.2

CPFP 5 34 6.8 20.3

Share of IDAD (%) 54.4 8.8 1.3 23.5

Source: IDAD Incentive Report (2016/17)

Notes: 1. SSAS approved 764 enterprises

The competitiveness investment cluster has tended to support smaller projects (R1.3 million on average) compared to the

services investment cluster (R8.2 million), manufacturing investment cluster (R12.8 million), and the broadening participation

cluster (R18 million). However, the competitive investment cluster average incentive value (R8.8 million) is more than that of

the services investment cluster (R6.8 million).

manufacturing Competitiveness enhancement Programme (mCeP)

The Manufacturing and Competitiveness Enhancement Programme (MCEP) was implemented in 2012 as a lifeline for

enterprises severely impacted by the 2008/09 global financial crisis so that they may retain employment, raise competitiveness

and secure higher levels of investment (DTI, n.d.).21 The R5.75 billion budget for the programme was fully expended by October

2015, resulting in its suspension. To date, MCEP continues to pay out claims. Two claims are paid out to firms: one at the

21 http://www.dti.gov.za/editmedia.jsp?id=3546



beginning of the project, within six months of the start of commercial production, and another upon the completion of the

project. During the 2016/17 financial year, 377 claims to the value of R989.2 million were paid. The DTI has been mandated

with the administration of MCEP grants, while the Industrial Development Corporation is responsible for administering MCEP

Loans.

export marketing and investment assistance (emia)

The Export Marketing and Investment Assistance (EMIA) scheme assists South African enterprises to develop export markets

for locally manufactured products and services. The incentive has four sub-programmes, namely: Individual Exhibition

Participation (IE); Primary Market Research (PMR); Individual Inward Missions (IIBM); and Foreign Direct Investment (FDI). The

total number of projects approved by the EMIA is 408 for 2016/17 with an incentive value of R32.1 million of which R22.3

million has been disbursed (Table 20).

Table 21 presents the approvals and value of disbursements for the EMIA incentive programme for SMMEs and large

enterprises, with SMMEs disaggregated by gender of the owner. The overwhelming majority of approvals were for SMMEs,

which accounted for 87.7 percent of all approvals and 89.2 percent of total project value.

The largest number of approvals in total have been to male-owned SMMEs, with 631 approvals for male SMMEs in 2013/14

falling to over 244 approvals in 2016/17. For the full period, male-owned SMMEs account for 53.9 percent of approvals and

56.5 percent of total project value. Female-owned SMMEs rank second in terms of number of approvals, with 281 approvals

in 2013/14 and 71 in 2016/17. Over the period as a whole, female-owned SMMEs accounted for one-third (33.8 percent) of

approvals and 43.5 percent of total project value. For the four-year period as a whole, the mean value of approvals for female-

owned SMMEs was almost R97 000, compared to just under R79 000 for male-owned SMMEs and R66 000 for large enterprises.

Table 21. emia approvals, 2013/14-2016/17

Year female male large enterprisesapprovals value

(R mil)ave.

Project value

(Rands)

approvals value(R mil)

ave. Project value

(Rands)

approvals value(R mil)

ave. Project value

(Rands)2013/14 281 25 88 968 631 24 38 035 101 5 49 505

2014/15 620 64 103 226 649 74 114 022 127 8 62 992

2015/16 197 18 91 371 341 28 82 111 103 10 97 087

2016/17 71 6 84 507 244 21 86 066 93 5 53 763

Average 292 28 96 664 466 37 78 820 106 7 66 038

Source: Data provided by the DTI (2016/17), DTI (2013/14, 2014/15, 2015/16)

Figure 17 shows the number of approvals under the EMIA by sector, distinguishing large enterprises from male- and female-

owned SMMEs. In 2016/17, EMIA approved 408 projects with the largest share of approvals (36.3 percent) in the Agro-

processing subsector. In the same period, 78.0 percent of all approvals were in four subsectors, namely: Agro-processing (36.3

percent), Chemicals (11.3 percent), Creative Industries (18.6 percent) and Electro-Technicals (11.8 percent).


figure 17. emia approvals by sub-sector, 2016/17

918

1419

21516

131

1219

457

1128

101

2519

1044

16

0 10 20 30 40 50 60 70 80 90 100 110

Textile, clothing and leather

Metals

Electro-technicals

Creative Industries

Chemicals

Automotive

Agro-processing

Aerospace

Male-ownedFemale-ownedLarge enterprise

Type of Enterprise

Source: Own calculations, data provided by the DTI (2018).

In terms of its scope of reach, Table 22 presents the total number of approvals and proportion of historically disadvantaged22

SMMEs (HDIs) that EMIA has supported in 2014/15 and 2016/17. The number of approvals in 2016/17 has dropped to less

than a third (408 approvals) of 2014/15 levels. Of the approvals in 2014/15, 56.1 percent were awarded to HDIs, this reduced

to 21.8 percent by 2016/17. The share of female owned HDIs in 2014/15 was 73.4 percent, and this rose to about four out of

five (79.8 percent) in 2016/17. Thus, amongst SMMEs covered by EMIA, there is a large representation of women. Of all HDIs

in 2014/15, three-fifths (59.5) percent were black females, while just over one tenth (11.1 percent) were white females. This

trend was reversed in 2016/17 where just over one in two HDIs were owned by white women, while three in ten (29.2 percent)

were owned by black women. In general, the proportion of female-owned HDIs is much larger than the share of male-owned

HDIs, once again indicating that this incentive has been successful in reaching women in small enterprises. It should be noted,

however, that HDIs in 2016/17 comprise little more than one-fifth of all incentives awarded by EMIA, indicating room for

further improvement of SMME coverage.

22 HDI firms and individuals are additionally defined as South African owned SMMEs that are 51 percent owned by black persons, women or disabled person(s). All other firms are defined as “other” under the EMIA programme and do not qualify under the definition of an SMME or HDI firm as defined by the EMIA Scheme.



Table 22. emia approvals by firm characteristics, 2014/15 and 2016/17

2014/15 2016/17

number share number share

Total Firms 1 334 100.0 408 100.0

HDIs 749 56.1 89 21.8

SMMEs 441 33.1 226 55.4

Others 144 10.8 - 0.0

Large Enterprises - 0.0 93 22.3

Share (%) of HDIs that were…

Female-owned 73.4 79.8

Black female-owned 59.5 29.2

White female-owned 13.9 50.6

Black male-owned 26.6 20.2

Source: dti internal data, 2014/15

Note: 1. The data did not report large enterprises for the 2014/15 year. 2. The term “Black” is used to denote African, Asian and Coloured individuals.

figure 18. Women-owned firms’ perceptions on emia

21 53 26

26 46 29

24 47 29

28 42 31

24 42 34

18 48 34

19 46 35

16 48 36

16 48 36

0 10 20 30 40 50 60 70 80 90 100Percent

Diversifying Export Destination

Maintaining Sales

Increasing Sales

Increasing Level of Exports

Maintaining Employee Levels

Increasing Production Capacity

Maintaining Level of Exports

Increasing Number of Products Exported

Increasing Employees

No impactSome impactSignificant impact

Extent of Impact

Source: DNA Economics based on survey of EMIA incentive beneficiaries (N=98).

The EMIA has been successful in stimulating employment and encouraging export participation for women-owned SMMEs.

Figure 18 presents the perceptions of the impact of the most recent EMIA participation for women-owned firms. The study

found that women-owned businesses identified a positive and significant impact of the most recent EMIA programme on

their export sales and ability to secure investment (DPME, 2014). More than two-fifths of women-owned firms reported

that the EMIA programmes had some impact on diversifying their export destination, increasing the number of employees,

increasing the level of exports, expanding production capacity, increasing sales, products exported and retaining employees

and sales level. In contrast, approximately one-third of the sample reported that the EMIA has made no impact towards the

performance of their entities.


sector-specific assistance Programme (ssas)

The Sector-Specific Assistance (SSAS) was established in 2009 to develop new export markets, to stimulate job creation and

promote broader participation of black-owned SMMEs in the economy. Trade and Investment South Africa (TISA) oversees the

Generic Funding component and IDAD manages both the project funding components of the scheme. The sub-programmes

of the scheme include Project Funding for Emerging Exporters, Project Funding (Export Councils, Joint Action Groups and

Industry Associations) and Generic Funding. In 2016/17, SSAS approved 52 projects approved under the CIC incentive which

included 764 enterprises receiving a total of R51.2 million in disbursement.

Figure 19 shows the proportion of approvals and the value of SSAS disbursements for 2017. From the lefthand panel it is

clear that female-owned SMMEs have received a larger share of approvals for all years but one: in 2016/17, more than half the

number of project approvals were for male-owned SMMEs (56.3 or 430 projects approved). The righthand panel shows that

the value of disbursements increased rapidly to 2014/2015—coinciding with the peak in approvals—before falling again in

the latter two years of the period. On average, the average disbursement per project was R54 707 in 2013/14 increasing to R67

015 in 2016/17.

figure 19. ssas approvals and disbursements, 2011/12-2016/17

369

417

403

723

361

456

430

334

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

Appr

ovals

2013/14 2014/15 2015/16 2016/17

Approvals

24

31

43

108

64

51.2

0

10

20

30

40

50

60

70

80

90

100

110

120

R milli

on

2011/12 2012/13 2013/14 2014/15 2015/16 2016/17

Disbursements

Male SMMEsFemale SMMEsTotal disbursement

Source: IDAD Incentive Report (2012-2017)

While financial assistance has varied over time, SSAS is important for creating and retaining employment across sectors. Figure

20 provides a disaggregation of SSAS approvals by sub-sectors with respect to gender for the financial period 2016/17. The

data indicate that more than two-fifths of approved projects were in the Creative Industries subsector (42.7 percent or 326

projects approved). During the same period, 69.9 percent of all approvals were in three subsectors, namely creative industries

(42.7 percent); textiles, clothing and leather (18.3 percent); and agro-processing (8.9 percent). However, approvals made in

each of the subsectors, except chemical industries and metals, were dominated by male-owned SMMEs. Roughly three-fifths

of approved projects in these two subsectors—58.3 percent in chemical industries and 61.0 percent in metals—were for

female-owned SMMEs.



figure 20. ssas approvals by subsector, 2016/17

59

6674

612

210

3623

19

849

154172

3525

2147

0 20 40 60 80 100 120 140 160 180Number of approvals

Multi-sectoral

Textiles, clothing & leather

Services

Mining

Metals

Energy

Electro-technical

Creative industries

Chemical industries

Agro-processing

MaleFemale

Gender

Source: Own calculations, data provided by the dti (2018).

As mentioned previously, women occupy relatively few jobs in manufacturing, mining and utilities industries. One of the

SSAS goals is to stimulate job creation and this can potentially be realised through financial support to SMMEs. In particular,

increasing support to women-owned SMMEs may help narrow the gender gap in employment.

Capital Projects feasibility Programme (CPfP)

The Capital Projects Feasibility Programme (CPFP) was launched in June 2003 to promote the exports of capital goods and

professional services through providing incentives for high-impact projects within and outside of Africa. The incentive is a

cost-sharing grant that is capped at R8 million, with the aim of facilitating feasibility studies that are likely to lead to high-

impact projects that will stimulate economic activity in South Africa. During 2016/17, five projects were approved for this

scheme with an incentive value of R34 million, of which R20.3 million was disbursed.

4.2.2.5. Infrastructure Investment Cluster

The Infrastructure Investment Cluster’s (IIC) main objective is to advance infrastructure development for investment purposes

(DTI, 2016). Infrastructural development is a critical means of development because it stimulates economic growth and

employment growth and promotes inclusive growth (NDP, 2011). This cluster consists of special economic zones (SEZs); the

critical infrastructure programme (CIP); and the cluster development programme (CDP). In total, the IIC approved 36 projects

to the value of R2 billion during the 2016/17 financial year. This cluster is projected to attract more than R3 billion in investment

and create 2 681 new jobs (Table 23). It is estimated to sustain 1 132 baseline jobs and promote investment by more than R3

billion.


Table 23. infrastructure investment Cluster, 2016/17

scheme Projects approved

incentive value(R mil)

ave. project value(R mil)


(R mil)

Projected new jobs

baseline jobs

Disbursed

(R mil)

SEZ 16 1 600 100 n.a.

CIP 13 310.9 23.9 3 000 2 681 164

CDP 7 65.9 9.4 18.6 1 132 10.8

Share of IDAD (%) 2.3 14.4 54.9 3.8

Source: IDAD Incentive Report (2016/17).

Note: Blank fields are due to data unavailability.

The infrastructure investment cluster tends to support bigger projects compared to other IDAD incentives clusters. This cluster

estimates 2 681 new jobs (under the CIP). However, the incentive value is higher at R14.4 million compared to other incentives

clusters which projects higher new jobs. Although the short-run employment and investment projections are not significantly

large compared to the amount invested, the outcomes tend to be broader than simply employment and are likely to only be

fully realised in the longer term.

special economic Zones (seZs)

Special Economic Zones (SEZs) target specific economic activities in preferred geographical locations. These economic zones

are supported by law or systems and may be sector-specific or multi-product (DTI, 2017). These economic zones are governed

by the SEZ Act No. 16 of 2014. The SEZ aims to attract local and foreign direct investment within these zones to encourage

international competitiveness (South African Revenue Services).23 The SEZs are categorised into free ports, free-trade zones,

industrial development zones and sector development zones (DTI, 2017). In 2016/17, 16 SEZs were approved with incentive

value of R1.6 billion. The average project value for SEZ was R100 million, this is 4.2 times average project value for CIP and 10.6

times CDP.

Critical infrastructure Programme (CiP)

The CIP was launched in September 2000 with the aim of promoting investment through the provision of infrastructure

development and lowering the infrastructure costs to encourage private sector investment (DTI, 2015; DTI, 2017). Projected

investment remained constant between 2011/12 and 2014/15, increasing sharply in 2015/16 then decreasing drastically in

2016/17 (Figure 21). This scheme has resulted in positive direct employment and construction employment between 2011/12

and 2016/17: averaged across the period, the scheme has supported 12 624 direct and construction jobs per annum.

23 http://www.sars.gov.za/ClientSegments/Customs-Excise/AboutCustoms/Pages/Special%20Economic%20Zones%20(SEZ).aspx



figure 21. CiP projected investment, projected jobs and disbursements, 2011/12-2016/17

Total direct and construction jobs


0

5

10

15

20

25

30

R billi

on / T

hous

ands

of jo

bs

2011/12 2012/13 2013/14 2014/15 2015/16 2016/17

Investment and Jobs

93

132140

81

100

164

0

20

40

60

80

100

120

140

160

180

R milli

on2011/12 2012/13 2013/14 2014/15 2015/16 2016/17

Disbursement

Source: IDAD Incentives Report (2016/17).

Cluster Development Programme (CDP)

The CDP was launched in April 2016 (pilot incentive) with the aim to encourage economic growth and employment creation

through collaborative projects from townships and/or industrial parks in former homelands (DTI, 2017). This incentive scheme

is in the form of a cost-sharing grant directed towards infrastructure, business development services and management

organisation of clusters (DTI, 2017).

In 2016/17, the CDP approved seven projects with a combined value of R65.9 million (Table 23). On average, each project

value was R9.4 million during this financial period. This scheme was linked to an estimated R18.6 million in investment and

sustained 1 132 jobs, or 3.0 percent of total IDAD baseline jobs. The CDP disbursed R10.8 million towards the projects.

4.2.3. dti Programmes with a Particular focus on Women

In addition to the dti incentive schemes, there are programmes which specifically target women to facilitate their participation

in the mainstream economy. Examples of such programmes include the Bavumile skills development programme, the

Isivande Women’s Fund and the South African Women Entrepreneurs Network, amongst others (DTI, n.d.). Women continue

to find themselves in a relatively disadvantaged position within the labour market and the economy in general, hence

these programmes serve to mitigate some of the obstacles that hamper women’s full participation in the economy. These

programmes encourage women-owned enterprises to contribute to the South African gross domestic product, employment

creation, equity and economic transformation (DTI, n.d.).

Figure 22 presents the budget allocation for some of the better-known of these programmes: Bavumile, SAWEN and Isivande

for the financial periods 2015/16 and 2016/17. SAWEN received the most funding of the three programmes over the reported

periods, reaching R19.1 million in 2016/17. In 2015/16, Bavumile received just R3 million in funding, just over one-third of the

funding received by Isivande; however, in the following financial year their positions were reversed, as Bavumile’s allocation

more than quadrupled to R13.0 million.


figure 22. Women-focussed programmes budget, 2015/16-2016/17

3.0

13.0

8.39.2

16.7

19.1

0

2

4

6

8

10

12

14

16

18

20R m

illion

Bavumile Isivande SAWEN

2015/162016/17

Financial Year

Source: DSBD (2016/17).

bavumile skills Development Programme

The Bavumile Skills Development Programme targets women who wants to pursue their own business by offering them

20 days of training on sewing, knitting, weaving and craft (DTI, 2011). The main objective of this programme is to advance

women’s skills and expertise in arts and craft in order to produce better products (DTI, 2011). The substantial expansion in

the budget between 2015/16 and 2016/17—effectively a quadrupling of the budget—was accompanied by a more than

doubling from 300 to 700 in the number of female entrepreneurs trained.

isivande Women’s fund (iWf)

The Isivande Women’s Fund (IWF) aims to enhance socio-economic development in rural, peri-urban and township areas by

empowering South African women (especially black women) through financial assistance of between R30 000 and R2 million

and non-financial support (DTI, 2011; n.d).24 The fund is involved with enterprises that seeks finance for start-up, for expanding

existing enterprises, for franchising, for business rehabilition and for gap finance (DTI, n.d.).25 The IWF supports SMMEs with

women ownership of more than 50 percent of the ordinary share capital and more than 30 percent in management positions

(DBSD, 2015 emb).

south african Women enterpreneurs network (saWen)

SAWEN is a Section 21 registered company under the dti, with the main objective to facilitate access to business resources,

information and opportunities for South African women enterpreneurs (SAWEN, 2012). This programme targets women

specifically, who engage in informal income generating activities and/or operate an SMME, or women who aspire to open a

business, particularly rural based women-owned SMMEs (SAWEN, 2012).

24 http://www.dti.gov.za/economic_empowerment/docs/women_empowerment/Towards_Enabling_study.pdf

25 http://www.dti.gov.za/economic_empowerment/women_empowerment_incentive.jsp?id=50&subthemeid=2



SAWEN was established to confront the challenges women entrepreneurs face in their business operations. The challenges

were classified into three broad categories, namely: gender, size of enterprises and general. In order to address these challenges,

this programme offers women entrepreneurs the opportunities for capacity building, business advice, business information

and networking opportunities, advocacy and lobbying (KZN Top Business, n.d.).26

4.3. summary

Access to credit is a key constraint to growth for entrepreneurs globally. In order to facilitate economic development, the IDAD

provides financial support to emerging or expanding businesses in the form of grants, loans or tax allowances. This analysis of

the incentive schemes offered by the IDAD indicates that there has been something of a structural shift in the composition of

approvals, from more projects with a smaller average value to fewer projects with a larger average value. This change is consistent

with broader policy debate on the role of Small, Medium and Micro Enterprises (SMMEs), which have been identified as a key

component to advancing inclusive growth and development in South Africa. In the National Development Plan, government

highlights the importance of these businesses for job creation, innovation and competitiveness, with the goal that 90 percent

of new jobs will be created by SMMEs in South Africa by 2030. This goal is in line with evidence that entrepreneurs are an

important source of job creation and that there are positive, long-term spill-over effects to entrepreneurship which serve to

increase employment growth rates (van Praag & Versloot, 2007).


First, it is important to match potential beneficiaries correctly to the incentive that would best meet their own business

needs. Second, where funds are awarded, it is important to ensure that the values granted and the length of the support are

commensurate with the business’s needs, as well as the broader growth objectives envisioned by the programme. This is key

to the overall sustainability of both the financing institution and the recipient firm. Third, efforts should be made to ensure that

marginalised groups are able to access initiatives intended for their empowerment. This may mean supporting the facilitation

of the process of enterprise formalisation, where appropriate.

Lastly, it is important to consider a set of incentives that are specifically designated for female entrepreneurs which will

attract and retain females, thus increasing overall participation and lowering poverty and inequality. This will enable national

policy agendas to have a greater impact on the individuals most in need of assistance. This necessitates a well-coordinated

policy strategy, with collaboration across different government departments, levels of government and relevant external

organisations. Such a coordinated approach is vital in the South African context, given the various interlinked challenges to

women’s full participation in the economy that fall within the mandates of a number of different ministries.

26 http://kzntopbusiness.co.za/site/kzn-top-businesses/South-African-Women-Entrepreneurs-Network/page/9956


5. DaTa To sUPPoRT THe genDeR analYsis of inCenTive PRogRammes

The original objective of this research was to conduct an analysis of the extent to which women benefit from the services

and funding provided by the various incentive schemes discussed above. In order to assess the impact of participation, we

proposed an econometric analysis that was to utilise (i) data drawn from individuals that applied to participate in the different

dti programmes and (ii) data relating to project outcomes. With data relating to applications, it would also be possible to assess

women’s access to dti programmes and compare it to that of men. In other words, with appropriate data it would be possible

to assess women’s access to these programmes and the factors that hinder or promote such access, and to gauge the impact

on relevant outcomes associated with participation in the programmes.

Unfortunately, during the research process it became clear that achieving the above objectives was significantly compromised

by the inadequacies of the available data. This consequently brought to light the need to interrogate the nature of the data

held by the dti from the perspective of a gender analysis, with the objective of proposing solutions that would facilitate such

an analysis in the future.

The approach taken here, with the link between data quality and monitoring and evaluation systems, is illustrated in Figure 23.

figure 23. a conceptual framework of data quality

Quality data

Monitoring and Evaluation System

Data quality dimensions

Availability, Usability, Reliability, and Relevance

monitoring and evaluation components

Component 1: Problem Analysis

Component 2: Theory of Change

Component 3: Intervention Logic

Component 4: Clear indicators, baselines and targets

5.1. Data Quality

The definition of data quality is widely debated in the literature. For instance, Wang and Strong (1996) define data quality as

“fitness for use” and emphasise the viewpoint of data consumers on what quality is, since they are the end users. Redmann

(1999, as cited in Gavin et al. (2011)) defines high quality data to be “data fit for their intended uses in operations, decision-

making and planning” and elaborates that “data are fit for use if they are free from defects and possess desired features”.

In defining data quality, the US National Institute of Statistical Sciences (NISS) (2001) gives principles of data quality to include:

One, data are a product, with consumers, to whom they have both cost and value. Two, as a product, data have quality,

resulting from the processes by which data are generated. Three, data quality depends on multiple factors, including (at least)

the purpose for which the data are used, the user and time. Four, data quality is multi-dimensional, and includes attributes of

intrinsic quality, accessibility, context and representation. Five, in principle, data quality can be measured and improved, but

the abstractions, techniques and software tools to do so are lacking. Six, human issues are central, because people are the key

links in the processes that generate most data. Seven, realisation of the importance of data quality is growing but inconsistent.

In the various definitions of data quality therefore the user and use of the data are a common thread, and there is consensus



that data quality is not synonymous to accuracy but is rather a multidimensional concept (Wang and Strong, 1996; Carson,

2001; and NISS, 2001).

In assessing data quality, it is common practice to present the data quality dimension considered in the assessment, which

often includes a varying number of data quality attributes. Wang and Strong (1996) define a “data quality dimension” as a set

of data quality attributes that represents a single aspect or construct of data quality. DAMA UK (2013) defines the data quality

dimension to be a characteristic, attribute or facet of data that can be measured or assessed against defined standards in order

to determine the quality of data. In data quality studies varied data quality dimensions are adopted, the choices made often

being based on the approach taken to study data quality. The three most common approaches are: one, an intuitive; two, a

theoretical; and three, an empirical approach (see Wang and Strong, 1996 for details).

Here, we adopt a mixed approach by combining the empirical approach and the intuitive approach. This is because, on the

one hand, the empirical approach captures the data quality attributes that are important to data consumers, who in this

case are the government departments, and enables us to determine if the data are fit for their use. On the other hand, the

intuitive approach allows us to offer expert opinion on what data quality attributes are desirable for an economic analysis as

had been commissioned. Our goal here, therefore, is to briefly discuss the data quality attributes that are of importance for a

gendered economic evaluation of the incentive programmes, and, where it is relevant in the current data, offer an appraisal.27

Accompanying the proposed data quality dimensions are examples of indicators that would be used in the measurement and

communication of the quality of data desirable for the exercise. Using the data requirement as a yardstick for the standard of

data with the user’s perspective at the heart of the framework, and mainly following the approaches by Cai and Zhu (2015)

and DAMA UK (2013), we adopt a hierarchical a data quality framework presented in Figure 24.

From the framework, having a checklist of quality indicators is the basis of ensuring that quality is not compromised. This is

because a satisfactory checklist would mean that the data quality attributes are adhered to satisfactorily; in other words, the

dataset meets the standards as stipulated in the good data quality dimensions.

figure 24. Data quality framework

Quality indicators or measures

Data quality attributes or

elements

Data quality dimensions

Source: Authors’ own interpretation of Cai and Zhu (2015).

27 This review is based on our interactions with dti staff and on our analysis of data provided by the dti.


We choose data quality dimensions that are commonly considered in the M&E of programmes and in typical economic analyses

such as the one that had been proposed. These dimensions are not cast in stone and could change depending on, say, the

future organisational needs of the department; and each of the dimension varies in level of importance. The dimensions are

then subdivided into a number of attributes or elements, and each attribute is accompanied by quality indicators or measures.

Ideally, and most importantly for this report, this framework serves as a pointer to the quality of data that was needed, and as

a guide in the assessment of good quality data.

In Table 26 we present the data quality dimensions, offer a definition for each one of them, and list the accompanying attributes.

For each attribute we furnish a number of quality indicators. These indicators form a checklist that would be instrumental in

identifying whether the existing data is of good quality.



Table 24. Data quality dimensions

Dimensions Definitions attributes examples of indicators

Availability The degree of convenience for users to obtain data and related information

1. Accessibility • Users can access the data • Data can be easily made public in one form or another, particularly

without sensitive information

2. Timeliness • Data can be provided within a given time frame and offer information on events/activities as they happened

• Data is regularly updated• Data collection interval serves the department’s requirements

3. Authorisation • Whether the department has the right to use the data

Usability The ease with which a database, dataset or data repository may be understood and accessed; how useful it is

1. Metadata • Whether the data has information about the physical characteristics of the datasets, such as location, record layout, database schemas, media and size

• Data has information about sample designs, questionnaires, software, variable definitions, etc.

• Whether the data is informative and useful• Whether the data meets the users’ needs

2. Validity • Whether the data conforms to the syntax (format, type, range) of its definition

• Data exist in range of known values and preferably as defined in the metadata

• Whether for each data item a comparison can be made between data and metadata or documentation

3. Credibility • Data comes from the statistics office of the government department or from the incentive beneficiaries

• Data is constantly checked for inaccuracies by officials

Reliability The level of trust that can be bestowed on the data

1. Completeness • Are all the components of the data recorded or captured• Are there missing values and if there are what is the explanation.

2. Consistency • There is no difference in a given data across different data items, records, datasets, and databases (for instance, information on a hardcopy application form matches that which is captured and stored in a computer)

3. Accuracy • Whether the data mirrors the world it represents as closely as possible

• Data minimises errors to a point of being negligible

4. Integrity • Whether the data generating processes is free from deliberate errors or manipulation for either personal or political gain

5. Confidentiality • Whether there is assurance to the programme participants that their data will be maintained according to national and/or international standards for data

• Evidence that personal data are not disclosed inappropriately• Data provided in hard copies is securely stored

Relevance The degree to which the database, dataset or data repository meets the current and potential future needs of users

1. Fitness • Whether the data collected can be used for the envisaged purpose• Whether data content relates to users’ expectations or demands

2. Adaptability • Data can be used for more than the intended use (i.e. it can meet potential future needs of users)

Source: Authors’ compilation and an adoption of Cai and Zhu (2015), DAMA UK (2013) and Gavin, et al. (2011).


5.2. existing Data limitations

The costs of poor quality data are both social and economic since they could affect an organisation’s reputation, affect its

performance and lead to loss of funds or revenue. In this context, the unavailability of good quality data meant we were

unable to undertake the proposed analysis. This was mainly due to the following data limitations:

5.2.1. Data collection, entry and follow-up

Currently, application forms seem to be the main means of data collection from the participants, and there seems to be no

follow-up to collect any other data, such as data to evaluate the beneficiaries’ enterprises performances post-funding. This

leads to a number of issues. First, if the application forms are not physically stored—which to some extent is likely due to

their bulky nature—failure to capture all the information in these forms means this information is lost once the forms are

disposed of. As discussed above, it is important that a system of data collection is in place, bearing in mind that the value

of good data collection can only be realised if the collected data is entered as accurately as possible and issues of missing

data minimised. This means that, first and foremost, all the data collected—such as that from application forms or progress

reports—should be captured, and that good data cleaning practices be employed. Such good data cleaning practices involve

the identification and elimination of errors that occur during data collection and entry. The data collection process needs to

be a shared endeavour by all stakeholders—the departments involved and the incentive beneficiaries—with the awareness

that they are both producers and users of the data. For this data to be usable and to ensure clarity in variable definitions, the

involved departments, as the main producers and custodians of the data, should provide a metadata offering descriptions

of the different aspects of the datasets. Ideally, a single metadata standard should be adopted across all government

departments to ensure consistency. This would facilitate the retrieval of precise and accurate information and ensure that

there is no misunderstanding or inconsistencies in the interpretation of the data.

Second, the collected data needs to be complete and be able to meet the needs of the users, something which requires

concerted effort from all stakeholders to collect the right data. For instance, in the proposed impact study by gender a host of

individual characteristics (such as, gender, age, race, disability status, geographical (province, rural/urban), educational level,

and sector for applicants/owners) of both applicants and participants, and outcome information (such as turnover; employee

information (gender, age, race, disability status, educational level); number of years in operation; type of business; share of

procurement spent on female business, CSR and on skills/ training for the firms themselves) was required. Most of this data

ought to have been held by government since most of it is information contained in the application forms. Yet, in spite of the

limited data provided by the departments and our efforts to augment this data with data available in the annual reports, it

was not possible to gather the minimum set of variables required for the impact analysis, and we were ultimately unable to

compile a meaningful set of baseline statistics on the dti programmes as originally envisaged.

Some of the specific data problems we encountered include the following:

• Only three out of 20 incentive schemes had data on gender;

• Employment numbers were only available in expected jobs created and not the actual jobs created;

• There was no clear disaggregation of the budget by each cluster, scheme and year;

• Data on unsuccessful applicants was not available; and

• Overall there was a lack of consistency in definition of concept, which, apart from creating confusion, made it difficult to

make comparisons between incentives and over time.

In our view, all this information should be collected through the application forms and follow-up reporting by the beneficiaries

with minimal effort on the part of those administering the programmes.



Third, there is need for consistency in the core information, such as demographic information and performance indicators,

collected across incentive scheme. This would require uniformity in the questions used to source this information and the

coding of such information in the data. The benefit from this is in ensuring that this core data is in the same format across

incentive schemes or any other programmes; in other words, it ensures compatibility and comparability.

Fourth, there seems to be limited engagement with beneficiaries of incentive schemes in terms of collecting the requisite data

to evaluate the performance of their enterprise and the impact of the incentives. Making data collection a collective effort by

all stakeholders is probably a route that those administering the programmes should consider, particularly given that most of

the information needed for any evaluation is in the custody of the beneficiaries. This would require that a reporting mechanism

be set up that would facilitate the collection of information. In setting up the mechanism it would be worthwhile to involve

beneficiaries since, besides the beneficiaries’ involvement in data collection, their contribution would be useful in defining the

agenda for evaluation; identifying key results and determining what constitutes a ‘successful outcome’; and analysing their

performance either for their own purposes or for purposes of the programme evaluation. Undoubtedly, this partnership in

data collection would facilitate and lighten the burden of monitoring and evaluating performance for all parties.

5.2.2. access to data and authority to use and share data

As both generators and users of data, government departments need to be able to use and share the data. As already noted,

the data generation process is one that involves different government department implementing parts of programmes or

whole programmes which may also affect other departments’ activities. This therefore makes a programme(s) outcome of

interest not to just the department implementing the programme but also to other government departments. For instance, in

this context, the incentives schemes considered in this report are mainly administered by the dti but their impact on women is

of interest to the DoW. This makes the access to the data generated of interest to all parties and consequently requires clarity

on right of use and who can share the data.

Overall, these data limitations can be dealt with by adhering to good data quality practices. However, it is important to note

that the fact that the data held by government departments is not perfect is neither a new phenomenon nor is it unique to

South Africa as it has long been acknowledged that many databases have errors (Wang and Strong, 1996). Going forward, it is

of paramount importance that good quality data is collected, captured and stored. This is critical if government departments

are to evaluate the performances of the various programmes they administer. The how of this process is best expressed in a

solid M&E design which embraces the above good quality data dimensions. This M&E design is discussed below.

5.3. The importance of Data within the Context of government’s m&e system

The South African government has in place a government-wide M&E system, the importance of which is noted in government’s

M&E Policy Framework (Department of Planning, Monitoring and Evaluation (DPME), 2011):

M&E processes can assist the public sector in evaluating its performance and identifying the factors which contribute to its

service delivery outcomes. M&E is uniquely oriented towards providing its users with the ability to draw causal connections

between the choice of policy priorities, the resourcing of those policy objectives, the programmes designed to implement them,

the services actually delivered and their ultimate impact on communities. M&E helps to provide an evidence base for public

resource allocation decisions and helps identify how challenges should be addressed and successes replicated.

Monitoring, the first component of M&E, refers to “collecting, analysing, and reporting data on inputs, activities, outputs,

outcomes and impacts as well as external factors, in a way that supports effective management” (DPME, 2011). Monitoring

is concerned with providing the relevant stakeholders with feedback on implementation and preliminary results or early

indicators of problems that need addressing.


Evaluation is a time-bound and periodic exercise that seeks to provide credible and useful information to answer specific

questions to guide decision making (DPME, 2011). Evaluations may assess relevance, efficiency, effectiveness, impact and

sustainability. Impact evaluations examine whether underlying theories and assumptions were valid, what worked, what did

not and why.

An M&E system is a set of organisational structures, management processes, standards, strategies, plans, indicators, information

systems, reporting lines and accountability relationships which enables national and provincial departments, municipalities

and other institutions to discharge their Monitoring and Evaluation functions effectively (DPME, 2011).

Critical for both of these components and for the system is the availability of relevant and timeous data. Such data would allow

not only evaluations to be made within the DPME’s Evaluations Framework but could find wider use as a departmental tool

for programme monitoring and refining.

To consider this further, we consider the outcomes based approach of the M&E system and note how data is integral to

this approach and the system. The four important components that underpin this approach are: problem analysis, theory of

change, intervention logic and clear indicators, baselines and targets (The Presidency, 2010).

Component 1: Problem analysis

This involves developing a clear understanding of the problem to ensure that the plan of action is relevant and addresses its

root causes. In this regard, data is required for us to first identify the problem, and second, to understand the nature or extent

of the problem. Data required to identify a broad problem is usually high level statistical data – for example, official Statistics

South Africa data that points toward high poverty and unemployment rates. To understand the dynamics and causes of the

broad problem, more specific data would then be required to understand the extent and nature of the problem. This type

of data should point toward a specific measurable goal. For example, what proportion of South Africans are unemployed or

poor? Where are these individuals located? Who are they: men, women, children? Understanding the nature of the problem

allows us to understand what needs to change (the intervention) and for who (the target group). Such data may again be

found from statistical data sources if possible, research done by others, an evaluation previously conducted or primary data

collection if no other means of interrogating the nature of the problem exist.

Component 2: Theory of Change

Having identified the problem and the nature of the problem (that is, what we want to change), we need to understand how

this change can be brought about. This involves developing a clear understanding of the assumptions behind choices and what

the key levers of change are. That is, we need to consider the available evidence and information relevant to addressing the

particular problem in formulating the response to a problem (the intervention). For example, in the unemployment example,

we would need to look to the available evidence on what types of interventions are successful in reducing unemployment

rates. Such evidence would include what has been found by governments in other countries through their experience,

through the academic literature that has considered this question, as well as previous South African government programmes

and what these have achieved. The question of how previous South African government programmes had fared may have

previously been addressed through an earlier evaluation.

Component 3: intervention logic

This refers to the assumptions about what must be done to achieve the outcome, how the results will be achieved and what

resources will be necessary. The previous component would assist us to describe, at a high level, what needs to be done to

achieve the targeted change.



For example, it may be found that a youth wage subsidy has been found to increase youth employment in other countries

as well as through trials which have been conducted in South Africa itself. However, to best implement the subsidy, we need

to understand further exactly how the intervention leads to the change. This would include an interrogation of, for example,

how the intervention should be administered. Do the youth receive the subsidy directly and the employer is then able to

deduct the claimed subsidy from the balance owed to the worker? Is the subsidy administered through the employer where

the employer pays the full wage amount to the youth worker and claims the amount back from the relevant authority? What

would be the problems associated with either of the approaches? Further, how do employers and the young workers respond

to the intervention regardless of how it is administered? Do employers increase overall employment or replace older workers

with younger workers? Do employers retain the youth workers they take on or simply replace workers on a frequent basis to

ensure they always have youth from which they can benefit from the subsidy?

The outcomes approach stresses measurable results. As such, the chain of logic must enable us to track progress and test

whether the intervention is sufficient to achieve the desired outcomes. The data implication of this is that data must be

collected to enable us to understand whether our assumptions were valid and if not, why not. It is not sufficient to know that

an intervention has failed or succeeded: we must be able to understand why this is the case so that the intervention can either

be improved or replicated with success in future.

Component 4: Clear indicators, baselines and targets

Indicators, baselines and targets provide the basis for monitoring progress and evaluating results and represent data that needs

to be collected as part of the process. Baselines are a description of the status quo, usually statistically stated, that provides

a point of comparison for future performance. Performance indicators are pre-determined signals that a specific point in a

process has been reached or result achieved. The nature of the signal will depend on what is being tracked and needs to be

very carefully chosen. In management terms, an indicator is a variable that is used to assess the achievement of results in

relation to the stated objectives. At each link of the causal chain, there should be a set of the indicators which allow progress

to be checked. Each indicator should have a clear baseline. The target is the measureable end goal that the intervention hopes

to achieve. It should be clearly defined with timelines specified. All indicators should be precise and measurable to enable that

the intervention can be adequately evaluated and the requisite data can be collected.

Table 25. Components of the outcomes-based approach to m&e and the relevant data requirements

Component Data requirement

Problem Analysis Data is required for us first, to identify the problem and second, to understand the nature or extent of the problem.

Theory of Change Evidence and information is required to understand how the problem can be addressed.

Intervention Logic Evidence and data is required to enable us to track progress throughout the intervention’s causal chain and test whether the outputs are necessary and sufficient to achieve the desired outcome.

Clear indicators, baselines and targets

At each link of the causal chain, there should be a set of precise and measurable indicators that allow progress to be checked. Each indicator should have a clear baseline. Targets and timelines should be clearly defined and data to measure progress with respect to these is required.

As it relates to data collection and the role of data in the M&E process, a number of particular principles articulated in the M&E

framework policy document (The Presidency, 2007) are also important in influencing how we think about data within this

realm.

The first of these is that M&E should contribute to improved governance. In particular, M&E processes should provide voice

to historically marginalised people and traditionally excluded interests should be represented throughout M&E processes.

The second is that M&E should be development-oriented: it should highlight the causes, effects and dynamics of poverty


and prioritise the interests of poor people. The third is that M&E should be utilisation oriented: M&E products must meet

knowledge and strategic needs and an accessible central repository of reports and indicators should be maintained. Read

with the first two principles, this suggests that data relevant to marginalised peoples should, where reasonably possible, be

collected as part of the M&E process. A further principle is that M&E should be methodologically sound: common indicators

and data collection methods should be used where possible to improve data collection and allow trend analysis; findings

should be based on systematic evidence and analysis; and methodology should match the questions being asked. This too

implies that data related to excluded groups should be collected where possible as advancing these groups is key to the

purpose of the process.

One way in ensuring that these principles are adhered to is that, wherever reasonably possible, race, gender and disability

status should be included as dimensions through which programmes are assessed, even in the cases where programmes

are not defined by theories of change that target marginalised grouped in specific terms. That is to say, if it is not costly

or unreasonable, data should be collected to allow us to assess the extent to which marginalised groups are impacted by

programmes and interventions as this is a pivotal underlying principle of government’s M&E system and what it aims to

achieve.

Below, we consider how this could be achieved using the specific example of how gender could be incorporated into a M&E

process for a generic incentive scheme to illustrate the data required to make an effective evaluation on the impacts of these

incentives on women’s participation in the economy.

Data is required from inception of the process—from identifying and understanding the problem—right through to the end

of the process, i.e. the evaluation of the intervention once it has run its course. Once the intervention has been understood,

but before it is implemented, adequate baseline data should be collected. We cannot evaluate whether an intervention has

been successful if we do not know what we are comparing the post-intervention results to, and for whom. With specific

reference to incentive programmes, and in particular to their impact on women, we need to know who the applicants are

(both successful and unsuccessful). The easiest way to do this, is to collate the application data. Information related to non-

successful applicants is important as it may allow an assessment of the factors related to failure or success in accessing finance.



figure 25. illustrative example of an m&e process incorporating gender 28be

foRe

inTe

Rven

Tio

n Problem identification

Statistics SA (QLFS) data to indicate the situation of women in the labour market and economy– particularly the problems that need to be addressed in this regard e.g. high unemployment rates or low entrepreneurship rates

dti Administrative Data to indicate where women are currently receiving funding so that the extent of the problem and current measures to address the problem can be understood

Evaluation Reports to indicate how incentives have previously benefited beneficiaries and to incorporate lessons learned from previous experiences into the intervention design

baseline

Company level data or individual owner data in the case of small businesses:

Identifier data (ownership data by various demographic characteristics, sector of operation, date operations started)

Number of total employed (disaggregated by gender and race and any other relevant characteristics)

Financial indicators (profit, turnover, debt and equity)

inTe

Rven

Tio

n inputs

The type of support applied for and received (Loan, grant or tax allowance)

Value of loan, grant or tax allowance awarded

Other costs of administering incentive e.g. workshops, staff, site visits

activities

A reporting schedule to be submitted by the beneficiary indicating the following: (i) whether the amount was received; (ii) the amount received; (iii) how the amount received was allocated amongst business activities; and (iv) indicators related to the specific activities undertaken in respect of the particular intervention (e.g. if workshops are part of the intervention, whether beneficiaries attended the workshops and the knowledge they retained could be relevant indicators in this regard)

afT

eR in

TeRv

enTi

on

outputs

Any relevant immediate output that results from the activities.

This may include, for example: Sales made; Employees employed; or Factories built.

These outputs will be dependent on the specific intervention.

outcomes

These are mid-term indicators following the intervention. These may include company level data such as number of total employed (disaggregated by gender and race); financial indicators (profit, turnover, debt and equity), and any other relevant data

This data should allow an assessment to be made on whether the intervention has contributed toward achieving any of the outcomes contemplated in the Medium Term Strategic Framework 2014-19.28

impact

An assessment should be made—based on the output and outcome evaluations—whether there has been a long-term developmental impact.

Broader national, provincial or local area indicators may be used for this purpose.

For example, an incentive that aims to increase employment of youth should, in the long-term, if successful, result in higher employment and lower unemployment rates in the area where it has been implemented. Labour force data collected by Statistics SA would be able to show whether this is true.

28 For dti incentives – and in specific reference to women - the most directly relevant broad Outcome is Outcome 4: Decent employment through inclusive growth. In particular, reference could be made to Sub-outcome 8 under Outcome 4: Economic opportunities for historically excluded vulnerable groups are expanded and the growth and development in small business and cooperatives is markedly improved.


For companies, data related to ownership, the sector they operate in, their current financial position and the details of their

employees are particularly relevant. As noted above, the data should be collected to take account of vulnerable groups, even

if the programme is not targeted at this group in particular. For assessing gender impact, this would mean that ownership data

and employee data, in particular, should be collected according to gender. For small businesses or individual entrepreneurs, the

same information should be collected, although gender information may be more easily collected with regard to ownership

for these smaller businesses.

For the successful applicants, data should be collected related to the following: the type of support they will be receiving (a

grant, loan or tax allowance); the value of this funding support; as well as the cost of other resources required to administer the

intervention. These are data related to the intervention inputs: all the resources that contribute to the production of outputs.

They include finances, personnel, equipment and buildings. Once the beneficiaries have been engaged by the dti, there

should be a schedule at which they submit relevant information that can be used to assess whether the intervention is being

used effectively. Such information is related to activities: the processes or actions that use the inputs to produce the desired

outputs and ultimately outcomes. Activities describe what is done and it is essential that the Department obtains data from

the beneficiaries which indicates how the funding is used by the beneficiary. This is necessary so that the theory of change can

be interrogated as well as the assumed logic chain. It is also necessary to isolate the effect of the intervention. For example,

if a particular intervention has been used to improve skills of workers in a particular division of a company, we would want

to access information specific to that division as we would not be able to isolate the effect of the incentive based on broad

overall company-level numbers. In essence, we need to understand how and where the funding is being used and indicators

related to that specific area of business operations will need to be collected to measure effect.

In this regard, the type of activities contemplated by the incentives should align to the theory of change for that particular

incentive. We note here that often theories of change do not explicitly take into account more vulnerable groups such as

women. In these cases, data are often not collected to allow a gendered analysis of incentives. As we have noted above, even

in those cases where incentives are not targeted specifically at women (or other marginalised groups), the data should be

collected. General theories of change can then be assessed with specific reference to gender. For example, an evaluation may

find that the assumptions of a theory of change are valid only for men and that the theory will need to be refined for women.

This would suggest a new incentive targeted specifically at women which takes the women-specific theory of change into

account; or a gendered stream of the broader incentive which takes the gendered nuances of the particular intervention into

account.

The final type of data that should be collected should assist in identifying the results of the intervention. These can be assessed

at three levels. At the most immediate level, outputs refer to the final products, goods or services produced for delivery

through the intervention. Examples include new jobs which have been created, increased production capacity or improved

cashflow or profits as a direct result of the intervention activities.

In the longer-term, outcomes stem from the outputs. These are medium-term results for specific beneficiaries which are

the consequence of achieving specific outputs. Outcomes are typically what was set out to be achieved at the beginning at

the process. For example, with specific reference to women, these could be increased employment of women or enhanced

viability of women-owned enterprises. Outcomes can be further categorized into immediate outcomes (something that occurs

shortly after the intervention) and intermediate outcomes (a result which is only observed sometime after the intervention).

In specific terms of the outcomes contemplated in government’s Medium Term Strategic Framework 2014-19, the relevant

broad outcome for dti incentives would be “Outcome 4: Decent employment through inclusive growth”. Further, under this

outcome, the relevant sub-outcome is “Sub Outcome Eight: Economic opportunities for historically excluded vulnerable

groups are expanded and the growth and development in small business and cooperatives is markedly improved”.

Impacts are the longer term developmental results of achieving specific outcomes and may be the result of many different

interventions aiming toward similar outcomes. Impacts refer to how communities and target groups have been influenced



and are stated broadly. Examples include improved economic well-being of citizens and lower levels of inequality. Importantly,

it should be possible to directly attribute intervention results (i.e. the outputs, outcomes and impact) to the intervention

inputs and activities. Precise and measurable indicators at each link of the causal chain which allow progress to be checked

are important in this regard.

We make a final note here on the type of indicators which should be used throughout the process. These will be different

for each specific incentive as each will have its own theory of change and causal logic which will need to be tested. What

is important is that the selected indicators are relevant, precise and measurable. Examples would include: the number of

employees, disaggregated by gender and race (where an incentive aims to increase employment—more likely for larger

companies) and financial indicators such as turnover, profit and debt ratios and measures of productivity such as production

per employee (where an incentive aims to improve viability or sustainability—more likely for small businesses).

Where appropriate, indicators may also be expressed on a “per received funding rand basis”; this would for example be an

indicator such as change in employment per rand received in funding; or as change in productivity per rand received in

funding. A positive indicator would be desired and the higher the number the better the effect of the intervention would

be assessed to be. Such indicators are particularly useful as they provide an indication not only of success but of the extent

of success, that is an indication of “value for money”. This would allow assessments to be made on where funding should be

focused to achieve greater impact.

5.4. summary

We have thus illustrated how important it is that high quality (that is, accessible, usable, reliable and relevant) data be collected

to enable effective M&E of government programmes. Lack of data, as well as poor quality data, often places limitations on the

types of evaluations and analysis which can be conducted in respect of government programmes. This often means that we

are unable to properly assess whether these programmes are achieving their stated objectives and whether they are having a

positive effect on the lives of the most vulnerable South Africans in particular.

The costs of poor quality data are both social and economic. Lack of data and poor quality data have the potential to affect

an organisation’s reputation, affect its performance and could lead to loss of funds or revenue. In the specific context of this

project, the unavailability of good quality data means that it is not possible to undertake the proposed quantitative gender

analysis of dti incentives without collecting primary data.

Our illustrative example of the type of data required to conduct a women-specific analysis of dti incentives within the

framework of government’s M&E system clearly illustrates the importance of quality data, as contemplated above, for M&E

purposes. We further note that our research, while itself not an evaluation exercise due to the lack of appropriate data, can add

value within this broad M&E framework. It is hoped that our findings, in this phase as well as the coming second phase of this

work, will inform M&E processes in the following ways:

• Identification of specific problems that may need to be addressed with respect to women’s participation in the economy

(especially considering that women were not part of the theory of change for most incentives and were thus not targeted

beneficiaries);

• Strengthening programme theories of change with specific reference to women;

• Strengthening the logic chain of the incentive programmes with particular reference to how the incentives impact on

women;

• Strengthening indicators, baseline data and targets; and

• Strengthening overall data collection and data processes.


These will however be addressed more specifically in section 6, in which we intend to investigate the extent to which women

benefit from the services and funding provided by the incentive schemes through interviewing beneficiaries.

Finally, we emphasise here that is imperative for the optimal functioning and benefit to be derived from the M&E system that

all eventual M&E activities be taken into account and built into government programmes up front. This requires clear M&E

planning undertaken at the outset of programme so that data processes, mechanisms and content are explicitly informed

by the M&E that will eventually take place with respect to the programme. If this is done, M&E will be facilitated: data for

monitoring purposes (and for picking up issues early on) will be available throughout the programme’s lifespan; and the data

may assist in strengthening the case for funding when it comes to budgetary applications.

Importantly, the initially envisaged quantitative analysis in this report would have been very straightforward to compile if

this type of approach to M&E was taken. Further, as this type of approach to M&E and data becomes more widespread, there

are potential synergies across government departments in terms of analysis, as well as in terms of identifying ‘packages’ of

interventions (i.e. combinations of interventions from different departments) that together might yield significantly stronger

results than either intervention on its own. An example would be the DoW and the dti collaborating on interventions to

improve the participation of women in the economy.



6. analYsis of THe seCToR-sPeCifiC assisTanCe sCHeme (ssas)

6.1. ssas overview

6.1.1. overview of the programme

Programmes under the dti’s Competitiveness Investment Cluster (CIC) are designed to promote structural transformation

in the economy, to encourage industrial dynamism and global competitiveness. As already noted, this cluster consists of

four schemes, each with their own focus; these schemes are: the Manufacturing Competitiveness Enhancement Programme

(MCEP); Export Marketing and Investment Assistance (EMIA); the Sector-Specific Assistance Programme (SSAS); and the Capital

Projects Feasibility Programme (CPFP).

The SSAS incentive was established in 2009 to foster industry- or sector-wide development with the specific objective of

growing new export markets, stimulating job creation and to broaden the export base (IDAD, 2016/17). Further, the SSAS

incentive aims to promote the broader participation of black owned SMMEs in the economy and to propose solutions to factors

inhibiting export growth (IDAD, 2016/17). SSAS funding is only available to emerging exporters who receive compensation for

all qualifying expenditure that relates to developing such firms (SSAS Programme Guidelines, 2013).

According to the dti (SSAS Programme Guidelines, 2013), the following characterises an emerging exporter:

• The owner(s) of the SMME must be South African;

• The entity should market a product or service that is EMIA qualifying, that is, one that develops export markets or will

attract increased foreign direct investment into South Africa;

• The business should be involved in domestic trading for 12 months prior to the application;

• The SMME must have been involved in some export activities or be considered to be export-ready;

• At least 51 percent of the entity must be owned by either of the following historically disadvantaged groups: females,

black person(s) and/or disabled; and

• The enterprise must have less than R25 million annual turnover in the year of application.

The SSAS incentive scheme comprises two main types of funding, which are overseen by different parts of the dti: Trade and

Investment South Africa (TISA) oversees the generic funding component, while IDAD administers the project funding element

of the scheme (IDAD, 2016/17). Generic funding is provided to export councils, industry associations and joint action groups

to sponsor activities that are likely to benefit all the members of that industry or sector. In addition, these funds also subsidise

the establishment, marketing and advertising activities of these industry or sectoral associations (DPME, 2014). By contrast,

project funding is channelled towards sponsoring specific marketing and sector-wide development projects overseen by the

export councils, industry associations and joint action groups (DPME, 2014). At this juncture, it must be stated that this section

focusses only on project funding supplied by IDAD as participants indicated receiving only this type of support.

In terms of gender, the SSAS guidelines do not distinguish between the treatment of female and male applicants and each

receive similar assistance and face the same application process and type of support (SSAS Programme Guidelines, n.d).

Despite this, women generally constitute the majority of those that receive support from the SSAS incentive scheme, as was

shown earlier in Figure 19. Over the full 2013/14-2016/17 period, female-owned SMMEs accounted for 55.3 percent of all SSAS

approvals.

The SSAS scheme funds 100 percent of the cost, to a maximum of R1.9 million per project, for local and international travel,

accommodation, flights, transportation of trade samples, preparation and freight of marketing materials, exhibition costs and

administration costs (SSAS Programme Guidelines, n.d). However, the SSAS incentive does not cover subsistence allowances,


visa fees and the cost of duties on products sold at the exhibition. All benefits are paid up-front for qualifying entities to the

approved service providers and will relate to all qualifying expenditure as approved by the EMIA Adjudicating Committee

(SSAS Programme Guidelines, n.d).

Like every incentive scheme, the SSAS has limitations in terms of the type of assistance offered (SSAS Programme Guidelines,

n.d). First, assistance is limited to entrepreneurs, while staff and consultants related expenses are excluded. This is done to

increase the impact of the funds by directly funding those elements that improve access to export markets. Second, a given

business’s participation is limited to four times per year. Officials at the dti indicated that this stipulation exists following the

understanding that growth in export markets requires repeated exposure. Third, the SSAS focusses on exhibition participation,

capacity building, missions and other related projects. Fourth, a minimum of ten and a maximum of twenty enterprises will

be funded to participate in a given project or mission. Fifth, at least 35 percent of the product should have a local content to

qualify for assistance. Last, submissions of applications should be done at least four months in advance. According to the dti,

a commonly reason for rejection of an application is that firms miss an application deadline and are asked to resubmit their

application for a later show. Firm applications may also be rejected for compliance issues—that is, they are not registered as

tax-payers with SARS or are not registered exporters—or where the firm has applied to attend a show that is in a different

sector to that indicated in their business registration documents.

6.1.2. How ssas is thought to impact firm outcomes

In our discussions with dti officials overseeing the SSAS incentive, the current theory of change was articulated as using the

incentive to develop an industry or sector, growing new export markets as well as stimulating job creation (IDAD 2016/17).

The idea is then that this increase in exports will translate to greater economic growth and better economic outcomes in the

country. This is supported in the economic literature which observes that exporters significantly differ from other firms and

exhibit various premia; for instance, they are often larger, pay better wages and have better jobs, the firms are more productive,

more capital-intensive and employ more skilled workers (Bhorat et al.,2017).

It can thus be inferred that the provision of SSAS support is to achieve the stated objectives of the incentive through

empowering SMMEs to grow their share of exports. The implied theory of change therefore is that these objectives will be

reached through small and medium sized businesses increasing their export activity.

While in principal the incentive appears to be pro-exports, it is unclear how firms are expected to develop their export share

beyond the additional exposure to these international and regional export missions. That is, while firms may attend up to four

missions a year, the incentive is largely silent on how these mostly small and sometimes medium-sized firms can conceivably

work to convert these leads into thriving exports. On a positive note, firms are largely responsible for developing new export

markets as they, in conjunction with their project coordinators, are responsible for identifying new export destinations and

then finding the most influential trade show to attend.

The existing theory of change is thus not very detailed and does not elaborate on how exactly the support provided and the

process involved therein will translate into the aimed for outcomes

In thinking through how the SSAS might impact outcomes for firms and their owners, it is useful to consider the process from

the perspective of firms. This is outlined in Figure 26 and can be split into six stages: awareness of the incentive; application

through the project coordinator; application outcome provided; event preparation and fund disbursement; the event; and

post-event outcomes.



figure 26. ssas process from the perspective of applicants

Awareness ApplicationApplication

outcome

Event preparation

and fund disbursement

Outcomes observed after

eventThe event

Each of these stages is discussed in greater detail below.

awareness of incentive

The process starts with the business becoming aware of the incentive. This usually takes place through an organisation

designated as a project coordinator. Firm owners who do not hear about the scheme will therefore be excluded at this point

of the process.

application through the Project Coordinator

The project coordinator will then serve as an intermediary between the dti and the enterprise wishing to apply to the SSAS

scheme. The project coordinator will assist applicants with the application process, ensuring that all the required documentation

is submitted and that the project applicant meets the criteria of the guidelines. Firms that do not meet the requirements—

and this would include all informal sector firms—are excluded from support. Similarly, firms whose applications project

coordinators might screen (or, simply, firms not notified by project coordinators of the opportunity) are also excluded from

support at this point.

application outcome Provided

Following this the application will be submitted to the dti who will either approve or reject the application, an outcome that is

communicated to the project coordinator to share with the applying firm. Based on interactions with the dti, we understand

that most applications will be accepted if they have been correctly and timeously submitted by the project coordinator. The

evidence suggests very few firms are excluded from support at this point of the process.

event Preparation and Disbursement of funds

Following acceptance, the dti will disburse the funds to the approved service providers to a maximum of R1.9 million per project

for preapproved expenditure relating to travel, accommodation, exhibition costs and other administrative costs.29 Effective

support from the project coordinator during the pre- and post-event could maximise the export outcomes beneficiaries

obtain from attending export missions. This support could come from the project coordinator before the event in the form

of assisting the beneficiary with their marketing materials and export marketing plan. Post-event, the project coordinator

29 In the case of the SSAS incentive what the beneficiary does with the received funds is pre-determined – for other incentives, there may be a further element of the beneficiary deciding how they will spend the funds received. This is particularly the case for incentives that provide beneficiaries with grants for starting or upgrading operations. For example, the Manufacturing Investment Programme (MIP) is a reimbursable cash grant designed to support textile and clothing manufacturers who intend to start-up a production facility, or to expand or upgrade the existing production facility. In this case, the beneficiary would have to specify whether they are starting a production facility, or expanding, as well as the extent of the start-up or expansion and what types of operations will be carried out by the facility. Similarly, the Aquaculture Development Incentive Programme (ADEP) provides a grant to a maximum of R30 million for qualifying capital costs, which goes directly to approved projects wishing to start-up or expand for enterprises involved in primary, secondary and ancillary aquaculture activities. The exact nature of the start-up or expansion is however at the discretion of the beneficiary applying for the grant and will be approved by the DTI rather than prescribed.


can work with the firms to convert the leads into sales and to follow up on other interesting leads obtained during various

networking sessions.

The event

The discussion here relates to how the beneficiary makes use of their attendance at the export mission including the

beneficiary’s experience at the event itself and the post-event support received from the project coordinator. At the event, the

beneficiary will showcase their products and, as noted from our interviews, they will potentially benefit in three main ways:

a. Exposure (leads accessed);

b. Networking (contacts made); and

c. Learning (experience and knowledge obtained).

Here again, effective support from the project coordinator could assist beneficiaries to maximise the benefits from their

attendance of the export mission. How businesses can potentially benefit from these three is discussed in more detail below.

Post-event observed outcomes

Beneficiaries are expected to benefit from the event in three ways: through the exposure gained, contacts made and learning.

For the business itself, each of these can be expected to lead to immediate to longer-term improved outcomes in export

performance, overall turnover and profitability. The direct and primary effect is the impact on exports. In the short-term,

exports can be increased can through leads that are converted into sales through the show.

However, exports can also be increased in the medium to long-term through sustainably growing or maintaining the export

sales made following the trade show where initial contacts convert into repeat business or where such buyers recommend

the business’s products to other foreign buyers. Thus contacts made at the show also provide a channel through which export

sales increase after the show. Exports can also be increased in the medium to long-term through what the business owner

has learnt through the experience. For example, they may refine their products to appeal to the export market based on their

new knowledge of the market. They may also adapt their business processes and operations in a manner that enables them

to access the export market better based on what they learn at the event.

In the medium to long-term however, there can also be an effect on domestic sales. The first channel through which this

could be achieved is through contacts made through the show which open local sales opportunities. These could be other

local exhibitors or relevant local stakeholders. For example, partnerships could be formed between exhibitors to stock each

other’s products or to jointly promote products locally. Any local stakeholders attending the mission may also become aware

of products showcased and become a link through which sales can be made locally. The second channel is through the

product improvements and operations refinements that are made from the knowledge obtained from the experience. While

the learning may be focused on increasing exports, there can be secondary complementary effects that serve to increase local

sales as well.

Finally, through the increased turnover (that may be the result of either the primary exports effect or the secondary domestic

sales effect), there are also potential “knock-on” effects that are to the benefit of South Africans other than the business owners.

These effects align with some of the broader dti objectives such as job creation and development of SMMEs.

6.1.3. The application process and project coordinators

Firms wishing to participate in the SSAS incentive scheme must apply for support through a project coordinator who acts as

an intermediary between the dti and the applying firm (SSAS Programme Guidelines, n.d). Applications from individual firms

will not be considered. The dti does not work directly with the enterprises, due to a lack of manpower and capacity to assist



the small businesses in finalising the requirements for the application process. Project coordinators are uniquely placed in

that they are aware of the dti’s requirements and the SMMEs’ abilities and can navigate both parties’ needs. The dti officials

responsible for overseeing SSAS applications indicated to us that, in the 2017/18 financial year, they received applications from

approximately 1 500 firms. Project coordinators therefore play an integral role from a logistics angle as they review and finalise

each of these applications ensuring they meet the application standards and deadline. Feedback on rejected applications is

also provided directly to the project coordinators who then share it with each of the applicant firms and work with them to

amend their application for consideration in later rounds.

All SSAS applications by firms should include a detailed exporter development programme that details how the SMME will

increase their export volumes in goods that continue to add value and contribute to job creation (the dti, 2013). Additionally,

this exporters programme should elaborate in detail how it will prepare participants before the event and specify the

envisioned post-event support. The application must also be accompanied by an exhibition brochure (SSAS Programme

Guidelines, n.d). The brochure includes the nature of the products exhibited by the participating entities and the profiles of

both the buyers and sellers. The project coordinator will prepare the export marketing plan and provide three quotations for

travel, freight, accommodation, exhibition costs and other expenditures (SSAS Programme Guidelines, n.d). It must be stated

that the support provided by these project coordinators is not part of the SSAS financial support paid to the applying firm.

However, as part of the SSAS emerging exporters scheme, project coordinators receive funding to compensate their role in

the provision of group marketing activities for emerging exporters (DPME, 2014).

Project coordinators that are eligible to provide this assistance to SMMEs include:

• Export councils established through application to the dti;30

• Industry associations;31

• Provincial Investment and Economic Development Agencies;

• Business Chambers;

• the Small Enterprise Development Agency (SEDA);

• Local municipalities; and

• Metropolitan councils (SSAS Programme Guidelines, n.d).

Based on data provided by the dti, in the 2017/18 financial year, there were 26 project coordinators that represented 611

entities applying for the SSAS funding. The shares of approved projects per type of project coordinator are presented in Figure

27. In the period under review, nearly half of the SSAS projects approved were applied for through industry associations (45.3

percent), while a quarter of successful firms applied through SEDA (24.4 percent). Of the reminder, similar proportions applied

either through the export council or provincial investment and economic development agencies.

30 An export council is a non-profit company under section 21 that serves the developmental and promotional objectives of a given industry on a national level.

31 An industry association is a body that serves the interests of an industry that is prioritised for development and promotion by the dti, as determined by the relevant customized sector desk and export promotion.


figure 27. ssas project coordinators by number of approvals, 2017/18

15.5

45.3

14.7

24.4

Export CouncilIndustry AssociationProvincial IAs & EDAsSEDA

Project Coordinator

Source: Own calculations based on data provided by the dti.

Once the application is received, a Senior Administrative Officer reviews the application and randomly assigns the specific

application to an internal team member who verifies the ownership status of the firm and determines whether the firm

satisfies the various compliance requirements (DPME, 2014). If the application is incomplete, it is returned to the firm which

has five working days to provide the outstanding information. Thereafter, the application is forwarded to the Adjudication

Committee, an internal committee that meets fortnightly and is tasked with the decision-making role of whether to approve

or reject applications made for SSAS support. The final decision is based on the dti Guidelines (2013) that sets the operational

boundaries for this incentive; that is, who receives support, the type of activities supported, the maximum funding payable and

the sectors that the applying firms must operate in. The final decision is relayed to the project coordinator who communicates

with the firm.

While firms may apply for SSAS support up to four times a year to increase the impact of the incentive scheme, dti officials

indicated that they may not apply for more than one dti incentive concurrently. This is to ensure that the same applicant firm

does not receive a large allocation of the total IDAD funding relative to other firms.

However, the evaluation of the data on SSAS approvals indicates that some companies were approved for SSAS support

more than four times within the same year. Figure 28 gives the proportion of companies approved for SSAS assistance, which

ranged from between one and seven approvals in 2016/17 and over both 2015/16 and 2016/17. While around three-quarters

of companies had only been approved once, there were companies which had been approved up to seven times in 2016/17.



figure 28. Distribution of firms by number of approvals received, 2015/16-2016/17

75.2 73.4

16.6 17.0

5.1 5.81.8 2.3 0.8 0.9 0.3 0.3 0.1 0.2

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

Perce

nt

Once Twice Three times Four times Five times Six times Seven times

2016/172015/16-2016/17

Year


6.1.4. Qualifying sectors

The choice of sectors that qualify for SSAS support is informed by the Industrial Policy Action Plan (IPAP), the dti’s premier

industrialisation and economic development policy document. These sectors are not fixed but can change based on the

structural changes to the economy and their resultant inclusion or exclusion in the IPAP. The sectors that are currently priority

industries for SSAS support are detailed in the dti’s SSAS Programme Guidelines (2013) as follows:

• Agro-processing;

• Automotive;

• Business process outsourcing services;

• Capital equipment and allied services;

• Chemical and allied industries;

• Civil engineering services;

• Consulting engineers;

• Creative industries;

• Electro-technical;

• Film production;

• Metals and allied industries;

• Pre-qualified ICT services; and

• Textile and clothing.


The importance of different project coordinators varies across these subsectors, as illustrated in Figure 29. In 2017/18 in some

subsectors, such as film and TV, mining32 and pharmaceuticals, all approved applications are from a single project coordinator;

in other subsectors, approvals come from a variety of project coordinators. Nine out of ten funded projects came from three

provinces, namely Gauteng (43.7 percent), the Western Cape (32.5 percent) and KwaZulu-Natal (14.5 percent). Compared

with their provincial shares of GDP—respectively 34.6 percent, 13.7 percent and 15.9 percent in 2016 (Statistics South Africa,

2018e)—Gauteng and particularly the Western Cape appear to be over-represented amongst funded projects.

figure 29. sectoral project approvals by project coordinator, 2017/18

47

37

15

67

33

55

2

23

20

28

50

40

4

13

53

30

100

6

44

50

100 100

35

65

54

31

15

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Perce

nt

Agro-processing

Automotive

Chemical industri

es

Creative industri

es

Electro-technical

Film & TV

MetalsMining

Pharmaceuticals

Services

Textiles, c

lothing & leather

Export CouncilProvincial IAs & EDAsIndustry AssociationSEDA

Project Coordinator


A disaggregation of SSAS approvals by sub-sectors with respect to gender for the 2016/17 financial period was presented

earlier in Figure 20. The data indicate that more than two-fifths of approved projects were in the creative industries sub-sector

(42.7 percent or 326 projects approved). During the same period, 69.9 percent of all approvals were concentrated in three

sub-sectors, namely: creative industries (42.7 percent); textiles, clothing and leather (18.3 percent) and agro-processing (8.9

percent). Meanwhile, approvals made were dominated by male-owned SMMEs across the various sectors. The exception to

this is found in the chemicals and metals sub-sectors. In both sub-sectors, three out of every five applications were made by

female-owned firms.

6.1.5. measuring impact

The dti, according to officials we spoke to, measures success according to various metrics. One measure is whether the firm

share of exports as a proportion of turnover has increased since application. Second, they consider the number of export

leads that the firm was able to convert into direct sales following the export mission. This directly enables the dti to determine

whether the country is developing new export markets. Third, whether the firm has created employment following the export

mission(s) is considered. Fourth, financial growth is an important marker. Here the dti is concerned with whether overall

turnover has grown post-SSAS support. Fifth, some of the firms that are supported did not have marketing or advertising

material prior to receiving support; after the export mission, they often have samples, marketing brochures and experience

with setting up stands at these trade shows. Post-support they have gained this vital experience as well as the actual samples

that they can use in further domestic and international marketing activities.

32 Although mining is not included in the thirteen priority sectors listed above, the 2018/19 IPAP lists mineral beneficiation as a priority sector.



According to dti officials, detailed information on the impact of SSAS is collected by the dti’s monitoring and evaluation

team who often prepare success stories on SSAS recipients as well as provide input into the IDAD’S Annual Incentive Report.

Twice a year, the SSAS team prepare a report on how disbursed funds were spent and the characteristics of supported firms.

Further, the project coordinators also collect any information on the impact of SSAS support to the recipient firms. We were

unfortunately not able to access this data or analysis.

6.2. Women in the ssas-eligible subsectors

In the earlier discussion of women’s position within the labour market, it was shown that women are underrepresented generally as a share of the labour force and, in particular, as a share of employment when compared to their 50.5 percent share of the working-age population (see Figure 8). The result is that women are overrepresented in unemployment relative to their labour force share, and account for just under half of the narrow unemployed. Within this broader labour market context, this section explores the situation within the SSAS-eligible subsectors.

Figure 30 presents employment by industry for the SSAS priority subsectors based on the 2016 LMD data. The largest subsector in terms of employment is civil engineering, which accounts for 21.9 percent of all employment within the SSAS priority subsectors. Civil engineering is followed by automotive (16.0 percent); agro-processing (11.7 percent); metals (10.9 percent); and textiles, clothing and leather (10.3 percent). ICT services sectors make up the largest share of employment for the group of dti identified industries, with a cumulative share of 68 percent of employment across these sectors. The smallest sectoral shares of employment come from the electro-technical (1.4 percent), film and TV (1.8 percent), and capital equipment (2.9 percent) subsectors.

Women account for a widely-varying share of employment within each of the twelve SSAS focus sectors for which data is available in 2016 (Figure 31). The figure shows that, in virtually all subsectors, women are in the minority. Women account for the smallest shares of employment in the metals (10.6 percent), civil engineering (11.1 percent), and automotive (11.9 percent) subsectors. This means that within employment in the metal sector, for example, there are 8.4 males per female. In civil engineering, the ratio is 8.0 to one, and in the automotive subsector it is 7.4 to one. The only subsector where women are in the majority is the textiles, clothing and leather subsector, in which only 0.5 men per woman were employed in 2016.

figure 30. Distribution of employment across ssas-eligible subsectors, 2016

10.3

10.9

8.1

1.8

1.4

3.7

7.3

21.9

4.3

2.9

16.0

11.7

0.0 5.0 10.0 15.0 20.0 25.0Percent


Metals

ICT services

Film & TV

Electro-technical

Creative industries

Consulting engineers

Civil engineering

Chemical industries

Capital equipment

Automotive

Agro-processing

Source: Own calculations, StatsSA, Labour Market Dynamics, 2016.

Notes: Business processing sector omitted as it is not possible to cleanly link the sector to specific SIC codes.


figure 31. female share of employment across ssas subsectors, 2016

40.4

11.9

23.6

38.7

11.1

19.2

43.5

29.5 28.832.9

10.6

66.8

1.5

7.4

3.2

1.6

8.0

4.2

1.3

2.4 2.5

0.52.0

8.4

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

Ratio (male:female)

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0Pe

rcent

Agro-processing

Automotive

Capital equipment

Chemical industri

es

Civil engineering


Creative industri

es

Electro-technical

Film & TV

ICT servic

esMetals

Textiles, c

lothing & leather

Female shareMale-to-female ratio


Notes: Business processing sector omitted as data on the sector is not available in the LMD Survey data utilised.

Table A 3 in the appendix provides more detail of the female shares of employment in these subsectors between 2013 and

2016. It confirms the civil engineering, metals and automotive subsectors as having the smallest proportion of females over

the period. The gender gap in capital equipment, though, fell sharply over the period from 6.8 males per female in 2013 to 3.2

males per female in 2016, suggesting a trend towards a more even gender distribution of employment within the subsector.

In analysing the impact of incentive schemes, an understanding on the demographic breakdown of sector is imperative. Figure

31 established that men dominate employment in all sectors aside from textiles, leather and clothing. Figure 32 illustrates the

gender ratio in employment for each race group across the SSAS-eligible subsectors in 2016. Further detail can be found in

Figure A 1 in the appendix. Within each subsector, the overall gender ratio of employment (male-to-female) is indicated by a

diamond-shaped mark—these are the same gender ratios presented in Figure 31—with those for each race group indicated

by the abbreviations AFR, COL, ASI and WHI (for African, Coloured, Asian and White). Ratios above one indicate that males

outnumber females within employment, while the opposite is true for ratios below one.



figure 32. gender ratio in employment by race across ssas-eligible subsectors, 2016

AFR

AFR

AFR

AFR

AFR

AFR

AFR

AFRAFR

AFR

AFR

AFR

COL

COL

COL

COL

COL

COL

COL

COLCOL

COL

COL

COL

ASI

ASI

ASI

ASI

ASI

ASI

ASI

ASI

ASIASI

ASI

ASI

WHI

WHIWHI

WHI

WHI WHI

WHI

WHI

WHI

WHI

WHI

WHI

0.1

1.0

10.0

100.0Ma

les pe

r fema

le in

emplo

ymen

t

Agro-processing

Automotive

Capital equipment

Chemical industri

es

Civil engineering


Creative industri

es

Electro-technical

Film & TV

ICT servic

esMetals

Textiles, c

lothing & leather

Total

Source: Own calculations. StatsSA, Labour Market Dynamics 2016.

Notes: Details of the race and gender composition of employment in each subsector are available in Table A 4 in the appendix. Vertical axis has a logarithmic scale.

Amongst Africans, the gender ratio is highest in the civil engineering (13.5 males per female), automotive (10.2) and metals

(8.8) subsectors. Similarly, for Coloureds, males are most dominant in metals (36.4 males per female), civil engineering (14.8) and

automotive (5.4). Amongst Asians, the ratios are highest in automotive (18.7), civil engineering (18.1) and capital equipment

(5.7), while for Whites the gender gap is larges in civil engineering (5.9), metals (5.4) and consulting engineers (4.8). It is clear

from these figures that the gender ratios for Whites tend to be lower than those of other race groups.

The subsectors also differ in the extent to which there is dispersion in the race-specific gender ratios. For example, in textiles,

leather and clothing there is little variation in the gender ratios, with Africans, Coloureds and Whites at 0.5 and Asians at 0.6.

In contrast, in metals the race-specific gender ratios range from 4.5 (Asians) to 36.4 (Coloureds), while in automotive the ratios

range between 3.5 (Whites) and 18.7 (Asians). In the chemical industries, creative industries and electro-technical subsectors,

the race groups have gender ratios on either side of one (i.e. for some races males dominate employment in the subsector,

for others females dominate). Thus, in chemical industries the gender ratio for Coloureds and Whites is less than one, while in

creative industries and electro-technical this is true for Coloureds and Asians respectively.

The gender gaps by race across the different SSAS-eligible sectors show that there are three to four sectors where the gender gaps in employment are particularly large and may need tailored sector-specific attention. These sectors are the automotive, civil engineering, metals and capital equipment sectors. The gender gaps in employment across sectors differ based on race, with the African, Coloured and Asian race groups showing particularly high male-to-fe-male employment ratios.


6.3. survey Results

6.3.1. methodology

6.3.1.1. Background

The SSAS incentive is applicable to the 13 subsectors that are prioritised in the IPAP. We set two main criteria in selecting the

sectors of focus. First, the subsector should not have been reviewed before. This disqualifies a subsector like film and TV, for

example. Second, the sector should have an interesting gender dynamic that would be worth exploring further. Based on

these criteria, the chosen sectors are: metals, agro-processing, chemicals and allied, and textiles. The gender dynamics of

these sectors will be discussed in further detail below, but it is worth highlighting the key characteristics here. In brief, the

chemical industries subsector has a high proportion of skilled workers, both male and female, although the former have a

higher proportion. The textiles, clothing and leather subsector hires many female workers and, across all skills levels, women

represent a greater proportion than men. The metals subsector is extremely male-dominated, while the agro-processing

subsector employs a large share of low-skilled women.

From these four SSAS subsectors, we randomly selected seven participating firms, ensuring a mixture of provinces, male- and

female-owned firms, as well as ownership across all four racial groups. Where firms were unwilling to participate, or where

we struggled to secure the interview, we randomly selected a replacement firm in their place. Interviews made use of the

questionnaire provided in Appendix IV were undertaken during June and July 2018. Of the 28 firms that were initially selected

to participate in the survey, we obtained responses from 21 which comprises the entire sample population for our analysis.

The interview guide was prepared to obtain the type of data that would be useful for this analysis. The data collection exercise

was also intended to show the types of data that can be gathered to serve the needs of various end-users. Hence, respondent

firms were asked about their firm characteristics, and their views on the following sub-themes: the application process; the

project coordinators who assisted them; outcomes and impact of the received support; and as broad questions on the status

of women across various measures. In some instances, the firms completed the survey unaided; in others, surveys were

completed over the phone assisted by a researcher. This did not appear to have any impact on the nature of responses given

as responses were quite similar across sectors and method of questioning.

Finally, as already noted, the SSAS has two elements: the generic funding component that is overseen by Trade and Investment

South Africa (TISA), and the project funding component managed by IDAD. Our analysis is restricted to the project funding

provided to emerging exporters as the respondents indicated that they had received support to attend export missions and

none of them when asked indicated that they had received generic funding.

6.3.1.2. Demographic and Labour Market Characteristics across Sampled SSAS Subsectors

Based on the 2016 LMD data, Table 26 presents the composition in terms of educational attainment of male and female workers

in the four SSAS subsectors. Within agro-processing, most workers have either incomplete or complete secondary education;

these two categories account for a combined 77.2 percent of female employment and 75.9 percent of male employment in

the subsector. Male workers in the sector tend to have slightly higher educational attainment than females, with the former

less likely to have only primary or incomplete secondary education.



Table 26. educational attainment of workers in selected ssas subsectors, 2016

agro-processing Chemical industries metals Textiles, clothing and leather

m f m f m f m f

Primary 9.8 10.7 6.2 2.6 10.6 1.8 14.4 12.1

Inc. secondary 38.9 43.4 24.4 24.2 39.3 29.0 44.2 51.3

Compl. secondary 37.0 33.8 49.5 39.0 36.8 43.8 32.0 28.9

Diploma, Certificate 10.0 9.5 11.8 25.2 10.0 21.1 6.0 6.8

Degree 3.3 2.1 7.4 8.3 1.6 4.3 0.7 0.9

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Source: Own calculations. StatsSA, Labour Market Dynamics, 2016

Notes: Figures are for males (M) and females (F) presented for each race within each subsector. Shares may not add to 100 due to rounding and the omission of other and unspecified responses.

In the chemical industries subsector, just under one-quarter of males and females have incomplete secondary education.

However, males in the subsector are more likely than their female counterparts to have a matric certifivate (49.5 percent

compared with 39.0 percent. However, this difference is more than made up for by the larger proportion of women with

diplomas and/or certificates: 25.2 percent of women in the subsector have this qualification, compared with 11.8 percent of

men. Women are also marginally more likely to have degrees. The high proportion of workers with complete secondary and

post-secondary qualifications in this subsector is a unique feature of a sector that is both capital intensive and dependent on

skilled workers.

In the metals subsector, more males than females have primary and incomplete secondary schooling (49.9 percent compared

to 30.8 percent). Women are particularly more likely than men in the subsector to have diplomas and/or certificates: roughly

one in five women (21.1 percent) have this qualification, compared to one in ten men (10.0 percent). Women are also more

likely than their male counterparts in the subsector to have degrees, although this educational category accounts for a small

proportion of employment.

The textiles, clothing and leather subsector stands out in terms of its relatively large proportion of workers at the lower end of

the educational ladder. Roughly three-fifths of workers in this subsector (58.6 percent of males and 63.4 percent of females)

have not completed matric. A further 32.0 percent of men and 28.9 percent of women have a matric certificate; thus, post-

secondary qualifications account for less than eight percent of employment, irrespective of gender.

Overall, the educational attainment of workers in the selected subsectors is quite similar. However, post-secondary qualifications

are more common amongst women in the chemicals and metals sector than in the other two sectors.

Closely linked to education attainment are skills levels. Figure 33 presents the skills levels by gender for the four selected SSAS

subsectors. Across all four sectors, semi-skilled occupations account for the largest share of employment. However, there are

various differences across subsectors. The agro-processing subsector, for example, has the highest share (approximately one

in three) of low-skilled workers. Unskilled males and females account for similar proportions unemployment (16.4 percent

and 16.2 percent). The chemicals industries subsector has the highest proportion of high-skilled individuals for both genders;

around three-tenths of workers in the subsector are high-skilled. Along with textiles, clothing and leather, metals stands out in

the extent to which it relies on semi-skilled workers; this skills category accounts for three out of four workers in the subsector,

the vast majority of whom are male. As already noted, textiles, clothing and leather is the only subsector in which women form

the majority of workers. This dominance is observed across all skills levels, with women outnumbering men by a factor of two

to one in both semi- and low-skilled occupations.


figure 33. skills and gender distribution of workers in selected ssas subsectors, 2016

9.25.1

34.0

19.1 16.4 16.1 16.913.0

31.9

15.6 12.4 10.1

12.6

2.3

69.6

6.1 7.22.3 4.5 6.0

23.7

50.3

5.010.4

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

High-skilled Semi-skilled Low-skilled High-skilled Semi-skilled Low-skilled

High-skilled Semi-skilled Low-skilled High-skilled Semi-skilled Low-skilled

Agro-processing Chemical industries

Metals Textiles, clothing & leather

MaleFemale

Gender

Perce

nt

Source: Own calculations using StatsSA, Labour Market Dynamics 2016.

The large number of unemployed youth (defined as those between the ages of 15 and 34) in the South African labour market

suggests that programmes, such as the SSAS, should have youth as a key target group. Table 27 presents the youth and gender

distribution of employment for the selected subsectors. According to the data, there is significant variation in the extent to

which the four subsectors employ young people, with the share of youth spanning a range of about 24 percentage points.

In agro-processing, over half (52.7 percent) of workers are youth, almost two-thirds of whom are male. In the three other

subsectors, however, youth are a minority in employment. The youth share of employment is roughly two-fifths in metals (38.0

percent) and chemical industries (41.5 percent), while just 28.4 percent of workers in textiles, clothing and leather are under

the age of 35.

Table 27. gender and age distribution of employment across selected ssas subsectors, 2016

subsector Youth non-Youth

male female Total m:f male female Total m:f

Agro-processing 33.9 18.9 52.7 1.8 25.8 21.5 47.3 1.2

Metals 34.4 3.7 38.0 9.3 55.0 6.9 62.0 7.9

Chemical industries 23.7 17.8 41.5 1.3 37.6 20.9 58.5 1.8

Textiles, clothing & leather 11.3 17.1 28.4 0.7 21.9 49.7 71.7 0.4


Notes: Figures are for males (M) and females (F), with the male-to-female ratio (M:F) presented for each subsector. Shares may not add to 100 due to rounding.

The only subsector in which women outnumber men in employment, whether youth or non-youth, is textiles, clothing

and leather. Within the subsector, women under 35 years account for 17.1 percent of total employment while their older

counterparts account for 49.7 percent. While the subsector is characterised by a favourable gender distribution of employment

from the perspective of women, it is also the oldest subsector with more than 70 percent of workers aged 35 years and older.



6.3.1.3. Sample Characteristics

Normally, it would be useful to compare the characteristics of the sample of firms to those of the full population that received

support over the period so as to be aware of any biases in the composition of the sample. Unfortunately, we are unable to do

this due to the restricted information contained in the data provided to us by the dti. Two main spreadsheets received from

the dti have been utilised in this analysis. The first that contained detailed information of the project coordinators has been

applied in section 6.1. The second is utilised in this section and contained the following information: the firm and owners’

names and telephone contacts; the province where the firm is located; its subsector according to IPAP; and information on the

owner’s race and gender. This is summarised in Table A 4in the appendix.

Table 28 summarises the demographic characteristics of the sampled firm owners and contrasts this, where possible, against

the fuller characteristics of the entire list of beneficiaries provided by the dti.

Table 28. baseline summary statistics of interviewed firms, 2018

Category share of respondents (%)

Gender Female 76.2

Male 23.8

Race African 57.1

Coloured 9.5

Asian 9.5

White 23.8

Nationality South African 95.0

No response 5.0

Disability No 90.5

No response 9.5

Age Youth (15-34 years) 19.0

… of which, 15-24 year olds 0.0

Non-youth (35 years and older) 76.2

Province Western Cape 28.6

Eastern Cape 9.5

Northern Cape n.a.

Free State n.a.

KwaZulu-Natal 19.0

North West 4.8

Gauteng 19.0

Mpumalanga 9.5

Limpopo 9.5

Highest educational attainment Matric only 19.0

Post-matric diploma 4.8

University degree (all levels) 71.4

Ownership profile Sole proprietor 66.7

Majority Owner 19.0

Minority Owner 9.5

Source: Own calculations based on firm responses.

Notes: The Northern Cape and Free State were automatically excluded from our sample as no firms in these provinces applied in the chosen subsectors.


Females represented two out of every five successful applicants (44.3 percent) in the population of supported firms. However,

the sample of interviewed firms had more females than males by a ratio of three to one (76.2 percent were female). Our sample

contained relatively fewer White owners than is observed for the population of supported firms: in the latter, 41.3 percent of

owners were White, compared with 23.8 percent in this sample.

In 2018Q2, more than half (53.1 percent) of the working-age population was aged between 15 and 34 years old (own

calculations, StatsSA QLFS 2018Q2). In this sample of firms, there were four times as many non-youth respondents as youth

respondents. Overall, the selected sample appears to be highly educated with seven in ten of these individuals indicating that

a university degree was their highest qualification. These figures differ significantly from that of the employed population, in

which only 10.6 percent have degrees compared with 32.7 percent that have only completed matric.

As expected from the definition of an emerging exporter the firms were all owned by South African nationals. Furthermore,

nine out of ten respondents indicated that they were not disabled; the remaining proportion did not respond to this question.

Lastly, respondents all indicated that they had turnover of less than R10 million in the year of application. As further proof

of their small size, two-thirds of the firms were run by a single owner with an average of seven employees at the time of

application (and an average of ten employees thereafter).

The three largest provinces in terms of their contribution to GDP—Gauteng, KwaZulu-Natal and the Western Cape—are home

to 90.3 percent of all firms that received SSAS support in the period under review. However, within the sample, they only

constitute 66.7 of the total sample, due to a deliberate choice on our part to over-sample other, often more rural provinces to

include a greater diversity of experiences and perspectives.

Overall, then, the profile of respondents is characterised as most likely to be female, African and aged 35 years and older. They

predominantly reside in one of the three major economic hubs and typically have degrees.

6.3.2. Results and Discussion

With a better understanding of the profile of the interviewed firms, we move on to discuss the findings from the data collected.

It is worth highlighting that a sample size of 21 firms is small and limits our ability to generalise the findings for a larger

population. However, even with this small sample, there are various emerging trends to be discussed. The section is discussed

across three timelines: at application, the short-term effects of the support and the longer-term impact of SSAS support.

6.3.2.1. The Application Process

As stipulated in the application guidelines, 85.7 percent of the businesses that applied had been operational for longer than a

year prior to applying to the dti for SSAS support. The remaining proportion were classified as being export-ready, qualifying

them to receive this dti support. Table 29 summarises when firms first applied for SSAS support. Approximately one-fifth (19.1

percent) of applications were in the past year, while two-thirds occurred in the last two to five years. Thus, 85.8 percent of

respondents reported applying in the last five years seeking support to attend a regional or international export mission.

Table 29. When did the business apply for ssas support?

Period share of respondents (%)

Last year 19.1

2-5 years ago 66.7

More than five years ago 9.5

Cannot remember 4.8




Project Coordinators are Crucial to the success of the ssas

Approximately half of respondents indicated that they had heard of the SSAS from either an investment or development

agency such as SEDA and Wesgro or from industry associations (Figure 34). Another source of information on the incentive

scheme that also plays the role of project coordinator are incubators and accelerators; 14.3 percent of firms applied following

the intervention of these entities that have access to export-ready firms and can assist them in putting together a successful

application. In those instances where firms heard of the support from the dti directly, the respondents indicate that they were

referred to other project coordinators to assist with the application process.

figure 34. Where did respondents first hear of the ssas?

4.8

9.5

9.5

14.3

14.3

19.1

28.6

0.0 5.0 10.0 15.0 20.0 25.0 30.0Percent

Networking Associations

Media

Referrals

Incubator/Accelerator

the dti

Industry Associations

Development/Investment Agency


Given the prominent role of project coordinators, it is unsurprising that over 90 percent of respondents were successful the first

time they applied for SSAS support. Unanimously so, the application process was categorised as being easy and straightforward

due to the fact they worked with experienced and knowledgeable project coordinators. In addition, the participants felt that

the process was simple enough that, with subsequent rounds of application, they were increasingly familiar with the process

and necessary documentation. While the guidelines are also easy to understand, one of the female participants noted that

they did not readily apply to agro-processing, which might indicate that there are some sector specific concerns that might

necessitate the revision of the form or the supporting documentation that firms must submit with their application.

Despite such positive sentiment, firms raised specific challenges faced when making the application. Firstly, it was noted that

the dti often provided feedback at the last minute which made it difficult for firms to plan accordingly. This finding slightly

contradicts the dti’s own view of the application process as they indicated when we met with them that their Adjudication

Committee reviews applications every two weeks and provide prompt feedback directly to the project coordinators to share

with the firms. If this is a capacity issue it is unclear whether it relates to the dti or the specific project coordinator. Secondly,

respondent firms indicated that it was quite onerous to collect and compile the accompanying documentation. As the majority

of the firms are classified as small, based on their turnover and employee size, even relatively easy application processes may

potentially strain firms’ very limited resources.

The most commonly cited reason for declined applications was that the specific event was oversubscribed and the dti could

not support any more firms to participate. However, as project coordinators can apply to send participants to up to four events

per year, such firms can always apply in the next quarter.


One drawback of using project coordinators to facilitate the application process may be the potential for gatekeeping (or the

perception of gatekeeping). This was alluded to by one respondent, who suggested that coordinators might choose not to

assist firms in the application process or share information on upcoming opportunities if they do not “like you/your firm”. For

this reason, the respondent indicated that they would prefer to deal directly with the dti. There is no evidence, though, that

this type of ‘gatekeeping’ is actually happening; nevertheless, such potential issues should be explicitly taken into account

when designing application systems and processes.

From our interviews with project coordinators, it appears that they are in direct control of applications going to the dti. The three

coordinators who agreed to be interviewed all confirmed that applications sent to the dti are based on the maximum number

of approvals per trade show. For example, if the dti will approve up to 15 applicants for a trade show in Dubai, the project

coordinator will send 15 potential candidates to the dti for approval. Both project coordinators who completed interviews

indicated that applications are very unlikely to be refused by the dti. Where applicants are refused, these are replaced by more

suitable applicants by the project coordinator. The most common reason for an application to be refused is if it does not meet

dti requirements. For example, the business owner may have been to too many trade shows to be eligible to re-application.

None of the project coordinators interviewed indicated the screening method used to determine which applications are sent

to the dti. However, one of the coordinators indicated that while they do not explicitly differentiate applicants by race and

gender, they take both race and gender into account when putting forward applications. They said that, at times, the dti may

ask for more black- and female-owned businesses if there are too many white male owners applying. One of the respondents

ended the phone call when asked how applicants were screened prior to submission to the dti.

Why do firms apply for ssas support?

A key focus of the SSAS is to provide support to emerging exporters within the various IPAP identified sectors to grow their

share of exports. However, respondents provide various reasons for their initial (or subsequent) applications. These include the

following:

• Export missions are an opportunity to undertake market research into potential markets and new display and marketing

trends;

• To identify and secure distribution partners and channels for their locally produced goods;

• As a means of diversifying into international markets where domestic demand is lagging in growth and opportunities;

• To increase their brand and product exposure to determine how their products fare against international competitors;

and

• To better understand a given country or region’s compliance or legal requirements for exporters wishing to distribute

goods.

Similar reasons were given by respondents irrespective of whether or not they had exported prior to their application, implying

that both sets of firms face similar challenges when considering diversifying into exports. According to respondents, the largest

barrier faced by firms is the significant cost of preparing and attending for these international trade shows or researching the

various needs and trends of the potential exporter markets. The greatest benefit from SSAS support is that it subsidises these

costs allowing firms to concentrate on improving their production volumes and quality of output.

Perceptions of male and female ssas applicants

As previously indicated, male and female applicants are not treated differently as the SSAS lacks an inbuilt process to distinguish

between them. Indeed, our analysis reveals that both groups of applicants heard of the incentive through similar channels—

trade and industry associations—and as stipulated in the dti Guidelines (2013) they made use of these institutions as project



coordinators to submit their applications. Additionally, both male and female applicants found the guidelines and application

process easy, straightforward and indicated that they greatly appreciated the assistance provided by the project coordinators.

However, three female respondents raised the following specific issues that they experienced during the application process.

First, was the length of time it took to put together the compliance documentation necessary to submit the SSAS application.

This is indicative of the small size of the business as the number of workers in this specific firm increased from one to three

post-SSAS support. Second, another respondent noted that the dti often finalises application outcomes too late for some firms

to make the necessary arrangements. This might be indicative of the large number of applications that the dti receives or a lack

of capacity in timeously processing received applications.

When asked for their reason for applying for the emerging exports support, male and female respondents cited similar reasons,

namely to grow their export markets, to identify distribution partners and channels, and to undertake market research. In

addition, female owners identified three additional reasons. These were to seek out new marketing or display techniques from

interactions at the international trade shows; for brand exposure; and to compare the quality of products produced locally to

those produced internationally.

Therefore, although the application process does not distinguish between male and female applicants, the motivation for

these firms applying for SSAS support reveals that there may be some intrinsic differences between these categories of owners

with regards to their operating environment that might require different pre- and post-SSAS support.

6.3.2.2. Quality of Support Received

Of the 21 respondents, 16 (76 percent) indicated that the assistance provided by the dti was sufficient. Four of these

respondents were men and twelve were women. One female respondent reported that it was sufficient “to an extent” and four

of the twenty-one (19 percent) indicated that the support was insufficient. Of these four, one respondent was a man and the

remaining three were women. Overall, therefore, 80 percent of men surveyed found support from the dti sufficient compared

to only 67 percent of women surveyed (twelve out of sixteen female-owned firms). The primary reason cited by firms that felt

the support was sufficient was because it covered all their travel and exhibition costs. Another positive outcome arising from

the support was exposure to international markets and an understanding of some of the compliance requirements necessary

to commence exporting to these markets.

At the same time, although these respondents believed the assistance provided by the dti was sufficient, some found it

difficult to finalise and close deals. Furthermore, some businesses realised that the standards of their samples and stands were

not comparable to those of entrepreneurs from other countries. Some female respondents also indicated that while they

were satisfied with the assistance received from the dti the notification period that was given to inform them that they were

awarded the funding was too short and they lacked sufficient time to prepare for the trade show.

Both project coordinators who completed the interview with us indicated that they perceived no difference in the needs of

male and female applicants, and that they required the same level of assistance throughout both the application and approval

process.

Proposed additional support

Four of the 21 respondents (19 percent) indicated the assistance provided by the dti was not sufficient. Three respondents

(all women) indicated that markets are different across the world and that the scheme is not designed to let them tap into

their target market (e.g. the US restaurant market), or assist with the distribution of goods across the world or locally. One

respondent felt that he had to do “everything himself”, which may indicate a mismatch between expectations and what the

SSAS is designed to do.


In response to whether firms would require further dti support, three female respondents (14 percent) indicated that they

would not. Four respondents (three females and one male) indicated that they would like assistance with market research or

marketing tools. Another female respondent indicated that she would like assistance with understanding tax, excise duties

and customs better. Six respondents (29 percent), four of whom were male, indicated that they would like assistance to

procure machinery (capital) to stimulate production for both local and international markets, and skills training for their staff.

This suggests that a large proportion of the men interviewed view capital as a constraint to their business and as a barrier

to growing export production. Another female respondent indicated that she would like business management advice and

business development support, including tips on how to follow up on leads received at conventions. Finally, four of the

respondents (19 percent), two of each gender, indicated that they would be interested in receiving funding support to expand

their businesses.

A review of the additional support that firms wish they could receive is informative as it shows on the one hand that firms

are aware of the other dti incentive schemes available to firms. For example, the firms that indicated that they had applied for

additional support from the dti requested consideration for inclusion into subsequent rounds of SSAS support; Employment

Creation Funding; the Agro-Processing Support Scheme (APSS); the Manufacturing Competitiveness Enhancement

Programme (MCEP); and for support through the Black Industrialist Programme. Apart from the application made for the APSS

and the black industrialist programme that are currently in the process, all the other applications were granted and individual

firms were satisfied with the outcome.

Some of these requests for additional support fall beyond the mandate of the SSAS objectives. Therefore it is incumbent on

the dti to create awareness of other avenues through which such support can be created for recipients of its incentives. This

may be through either creating awareness of other relevant incentive programmes and sharing these with firms and project

coordinators or expanding the current mandate of SSAS to include a business support and capital funding element.

although mostly sufficient, additional support required from the project coordinators

Of the interviewed respondents, eight respondents (38 percent) stated that they received no support from the project

coordinator. Of these, half were female. It is unclear as to whether these respondents requested support and did not receive it,

or if support was simply unavailable to them. Six (29 percent) of the respondents indicated that they received active support

from the project coordinators and five of the six respondents that sought additional support were female The support received

took the form of guidance on how to improve local sales and how to use foreign contact to improve their business, the

importance of marketing tools such as catalogues, and key requirements for trade shows. This was in addition to courses run

on various aspects of small business development.

The assistance also differed across the different sectors under review. For instance, a female respondent from agro-processing

indicated that the project coordinator in her sector was proactive in informing her about future trade shows and similar

events. In the chemicals industries, a male respondent indicated that the project coordinator also mentored business owners

and ran several workshops. In metals, a female respondent indicated that the project coordinator requested a sales report and

a comprehensive monthly report on the status of the business. One female respondent from textiles, clothing and leather

noted that the CCDI, as a not-for-profit company did not form part of the dti coordinators who receive funding, so support

was unavailable. On the other hand, a male respondent from the same industry indicated that the project coordinator did not

provide correct information on the objective of the trade mission and the correct products that could be displayed, something

that could be improved. A female respondent from the metals industry in Gauteng was particularly satisfied with the support

received from the project coordinator stating that she received assistance with everything she needed.

The input from respondents on the ways in which project coordinators could improve the support provided varies across

the four sectors, but relates to the following common themes. Firstly, with regards to preparing for the export mission, a

female respondent in agro-processing raised the need for assistance in networking skills necessary to engage with other



trade exhibition participants to maximise on the little time they have to interact when they are not supervising their own

stands. Another female respondent from agro-processing also raised the need for a pre-mission gathering so local exhibitors

and field experts can network with each other and so that collectively they can develop a marketing strategy for that mission.

This would have the added benefit of equipping business owners with the right skills to create networks and knowledge of

processes applicable to their sector. Respondents within textiles, leather and clothing, and the chemicals industries requested

support in preparing marketing materials and ensuring that they are of good quality and meet industry standards.

Secondly, there were various proposals around capacity building workshops. These would touch on various aspects of business

development and management. For instance in metals, a respondent noted that they would like additional information on

how to maximise their participation at the trade shows. Another female respondent indicated that they would like assistance

on how to follow up on leads and contacts and convert these into sales. This was raised by a number of respondents implying

that a further intervention is required beyond exposure to international markets up to four times a year.

Thirdly, although out of the scope of the project coordinators, some respondents requested financial support. A male

respondent in the agro-processing industry indicated that they would have liked to receive more support, in terms of funding

for capital, and global accreditation for greater participation in the export market.

It appears then that, although project coordinators assist the firms post accessing the support, the nature and intensity of this

assistance varies across sector according to the project coordinator’s experience, knowledge and the number of firms that

they are overseeing. Overall, the challenges faced in terms of support from project coordinators run along the same themes

for the male and female respondents of the survey. They both require additional support with marketing and preparation for

trade shows, with more men indicating that they would like support in terms of capital acquisition.

barriers to female entrepreneurs in establishing successful businesses

Most respondents interviewed in metals were female and working mainly as jewellery designers and producers. While one of

these female respondents indicated that women in the jewellery business faced few barriers, other respondents stated that

access to markets and finance posed a key challenge. More specifically, knowledge relating to basic business administration

seems to be a challenge for female respondents, particularly around providing quotes and invoicing. With regards to finances,

the respondents cited the high start-up costs associated with setting up jewellery production as limiting entry into the sector.

In agro-processing the challenges for female entrepreneurs seem more prominent. The industry is male-dominated and,

according to the five female respondents interviewed, it is very difficult for female entrepreneurs to access funding. There

also seems to be an unwillingness or reluctance from men in the industry to engage with female entrepreneurs, making it

challenging for women to partner with men to finalise deals. In the respondents’ opinion, there seems to be a lack of trust in

the technical capabilities of women in agro-processing, resulting in a reluctance to enter contractual arrangements with them.

Women in the sector have also reported disrespectful and patronising behavior when engaging professionally with men, with

the general feeling being that men feel women are incapable of understanding agriculture or running an agro-processing

business profitably.33 This implies, as indicated by another respondent, that it becomes challenging to create a network as

most men prefer to work with other men and women are very often overlooked. Without a strong network, obtaining raw

materials and assistance with the distribution of goods becomes costly and time consuming.

The textiles, clothing and leather subsector is female-dominated, although our sample included an equal number of male

and female respondents. In this industry, unlike most others, women seem to be at a trade and business advantage. However,

the respondents did highlight several barriers that female entrepreneurs in the industry face. The first is a lack of marketing

skills: it seems that while they can produce quality output, there is an inability to translate production into sales due to a lack

of marketing knowledge. Other challenges female entrepreneurs face in this subsector, according to a male respondent, are

33 The single male respondent, out of a total of six respondents, supported the perception that female entrepreneurs lack experience in the industry.


a lack of funding, restricted market access, limited knowledge and expertise, and limited mentoring opportunities. Female

respondents also note that they are not taken as seriously as men in business related matters with the result that they often

work harder to be considered credible.

In the chemicals industries there were five respondents, four of whom were female. According to a female respondent, the

barriers faced by women seem to be no different from the barriers faced by men and include a lack of funding and difficulty

in penetrating markets. The male respondent indicated that there is also a lack of information about the sector available to

women and, in his opinion, a lack of support for women. Further, a female respondent noted that with the market being

extremely competitive it is difficult to gain credibility as a new entrant into the market. In this subsector there also seems to

be high operating costs which act as a barrier to women who struggle to access funding; this was also reported by a female

respondent.

Similar support is suggested by both male and female respondents to encourage greater female participation. This included

promoting greater awareness of dti incentives, organising workshops for small business owners on various topics, encouraging

greater access to funding as well as mentorship and business coaching. Our discussion of the quality of the support provided

to women provides insights into various sector-specific issues that limit the growth of female entrepreneurs. These mainly have

to do with perceptions of women’s technical and product knowledge which result in their being locked out of networking

and partnering opportunities within the sector which further limits growth and expansion opportunities. Therefore, while

the type of support provided is sufficient in that, it fully covers the cost of participating in international trade missions, as an

incentive that seeks to foster industry- or sector-wide development the quality of support offered is lacking because it fails to

fully address the issues faced by businesses within the sector that will limit their ability to grow export production.

6.3.3. impact of the ssas

The nature of the impact of the SSAS on participating firms is a key consideration. In measuring how the turnover of

participating firms had changed between their application for the support and the most recent period after the support had

been received, we expect that turnover might have been affected in two possible ways: first, through the direct channel of

export markets accessed through the export shows, and second through the improved product and business processes as

well as contacts made because of the export shows.

impact on exports

We consider first how the export performance of the firms changed after the support was received and whether this can

reasonably be attributed to the SSAS incentive received. It must be reiterated that the specific effect of the incentive is difficult

to isolate from other factors that may have contributed toward export and turnover changes, particularly when this exercise

is done retrospectively as in this case.

Table 30 presents information on the extent of engagement in exports by the respondents, before and after their participation

in the SSAS and in relation to the change in their turnover over the period. Prior to participation, ten respondents had not

exported before, eight did export (all only occasionally or only to a small number of international customers), and two exported

in only some years. In total then, only ten of the interviewed beneficiaries had ever exported before.



Table 30. Change in export share and turnover pre- and post-ssas participation

nature of export share export share Change in turnover (pre- to post-ssas)Pre-ssas participation Post-ssas participation

No export activity at all 7 firms indicate no export activity 7 firms state no export activity No change

Some export activity Firm exports less than 10% Firm exports less than 10% No change

Firm exports 5% Firm exports 5% Increased

Firm did not specify amount but indicated that there was no change

Firm did not specify amount but indicated that there was no change

Decreased

Enhanced export activity Firm did not export Firm exports 5% Increased

Firm did not export Firm exports 15% Increased

Firm did not export Firm exports 90% Increased

Firm exports 1% Firm exports 4% Increased

Firm exports less than 10% Firm exports 30% to 40% No change

No response 6 firms did not respond 6 firms did not respond All increased


Overall then, five of the 21 respondents reported an increase in their export sales as a proportion of total turnover. Four of

these were female (out of 16 females). One of these was a male (out of five males). Importantly, however, we need to consider

whether improved export outcomes for these five respondents can be (directly or indirectly) attributed to the SSAS incentive.

Direct channel

With respect to the direct channel through which the SSAS aims to lead to increased exports, we consider the number of leads

received at the show and whether these leads were converted to sales. Across all respondents, 16 of the 21 respondents (12

females and 4 males) indicated they received leads; and of these, eleven indicated that the converted these into sales (Table

31). These included eight of sixteen females and three of the five men. Thus, across both men and women, around eighty

percent of respondent achieved leads, while around half of all respondents achieved sales from these leads.

Table 31. number of leads and conversions into sales

number of leads number of respondents outcome number of respondents

that made a sale

1 21 stated that their business partner received one lead that was converted into a sale 21 stated that one sale was made from the lead

2-5 4

2 stated that no sales arose from leads

21 reported one sale

1 reported two sales

6-10 4

2 stated that no sales arose from leads

21 reported one sale


11-20 4

1 stated that one sale arose from the lead


1 reported more than 10 sales

1 reported 16 sales

21-30 21 states that no sales arose from the leads

11 reported 4 sales

Total 16 11



Ten respondents reported the value of sales from leads made at the export show. Values of sales ranged between R5 000 to

R150 000. Six of these respondents reported sales values less than R15 000 (with the average being R7 300 for the six). The

remaining four respondents achieved sales that were more substantial: one reported achieved sales of R29 000, another R80

000, another between R50 000 and R100 000 and one R150 000. The three respondents who reported the highest value of

sales were in the textiles manufacturing sector. Two of these were women. This suggests that the export show perhaps has

been most impactful (at least in terms of direct impact) for the textiles sub-sector and that women in this sector have been

able to achieve substantial exports through the show.

indirect channel

To understand how the export show benefited businesses, apart from just exposing them to potential buyers, we also tried to ascertain how businesses had learnt from the experience and whether they gained any useful contacts from the show. This can be considered as the indirect channel through which the SSAS serves to increase exports in the longer run, in contrast to the direct channel through which export sales are achieved through leads obtained attendance of the export show itself. In this regard, we asked respondents whether they had marketing materials such as brochures and product samples before and after making the SSAS application, as well as whether they had exporting marketing plans.

Of the 21 respondents, 16 indicated that they had marketing materials both before and after the application and show. The remaining respondents did not answer this question. No one indicated that they did not have these marketing or promotional materials before the application but had them after. This then did not seem to be a factor that changed through the process or event that would have any bearing on the outcomes observed.

In terms of product samples, 12 out of 21 respondents indicated that they had samples before the application, while three indicated that they did not. After the application, 13 of the 21 respondents indicated that they had product samples. The one respondent who has samples now but who did not have at the time of application was a female respondent in the metals subsector. Her exports and turnover have increased from the time of application suggesting a correlation between applying for SSAS support and these positive business performance effects. Two of the three respondents who indicated they did not have any product samples before the show indicated that they still did not after the application. Six respondents did not answer this question. Overall then, there seems to be some suggestion that product sample enhancement through SSAS may be a channel through which SSAS can serve to increase export and performance; however, this is based on the experience of a single respondent.

Ten of the respondents indicated that they did not have an export marketing plan before the application; six indicated that they did. After the application and show, 11 indicated that they had an export marketing plan (although one of these indicated that it was currently being developed). Five indicated that they still did not have an export marketing plan after the application and show. Five respondents did not answer this question.

Of the five respondents who indicated that they did not have an export marketing plan before the application but had one after, four increased their exports as a percentage of turnover from when the application was made to the most recent year. All four of these businesses converted leads from the export show into the sales. In terms of positive gender impact, three of these four respondents are female; one in the metal subsector and two in textiles. Of the six respondents who had an export marketing plan before and after the application, only one—a female respondent in the metals sector—reported an increase in exports as a proportion of total turnover. All six of these, however, reported having converted leads from the show into at least one sale.

In total then, ten out of the 11 respondents who currently have a plan achieved some exports through the show and five reported increased exports as a proportion of turnover. Of these five, four were respondents who did not have an export marketing plan prior to their application. This suggests that there may be a link between having an export marketing plan and increasing exports. However, these findings slightly contradict with the SSAS application requirements that require the project coordinator to supply an export marketing plan for each business as it appears that a large share of the recipients received funding without this document.



Fifteen of the 21 respondents indicated that attendance at the event increased their knowledge of their buyers’ business,

regulatory and cultural context. One respondent said that it did not increase their knowledge of these “that much”. Five

respondents did not answer this question. Of the fifteen respondents who said that the event increased their knowledge

of their buyers’ context, ten managed to make export sales through the show. In terms of exports in the most recent year,

however, only four reported a higher proportion of total sales being exports than before the application was made, suggesting

that other barriers to becoming exporters exist or that the link between understanding the buyers’ market and exporting to

that market is not very strong.

impact of Turnover

Both direct and indirect effects of the incentive should be visible if the incentive was successful through an increase in turnover.

Turnover would be increased through greater export sales (either through the direct or indirect channels considered above),

as well as possibly through positive effects on the business’s products and functioning through contacts made, and learning

and refining through the experience.

At application, all the businesses were classified as small, reporting an annual turnover of less than R10 million. In the most

recent year, however, two respondents reported being medium-sized businesses. Both firms were owned by male respondents

(one in agro-processing and the other in textile manufacturing). The rest were still classified as small businesses in the most

recent financial year.

Of the 15 firms that reported turnover values, fourteen indicated that their turnover had increased while one female owner

stated that their turnover had declined slightly (Table 32). Of these, 13 are female-owned enterprises and two are male-owned

enterprises. We cannot directly attribute these changes in turnover to the SSAS incentive as many different factors contribute

to changes in turnover and we are unable to isolate the effect of the incentive on turnover especially where this was not

explicitly tracked by the businesses or the dti.

Table 32. firms’ turnover at application for the ssas and for most recent period

subsector Respondent’s gender Change in annual Turnover (%)Agro-processing Female 500

Agro-processing Female 154





Metals Female 69

Metals Female 268

Metals Female 520

Metals Female 1400

Textiles, clothing & leather Female 2500

Textiles, clothing & leather Male 77

Chemical industries Female 180

Chemical industries Female -8

Chemical industries Male 40


Notes: 1. Of the 16 firms that reported turnover numbers, one firm reported turnover only for the most recent year as they had not started operating when they made their application. 2. Of the five firms that reported turnover according to firm size, only one changed size, going from small (turnover of less than R10 million) to medium (turnover greater than R10 million but less than R50 million). The remaining four firms were small both at the time of application and in the most recent period.


To determine whether the respondents felt that any change in turnover and their financial position was due to the SSAS

support received we asked them about their profitability before and after their application as well as their plans for expansion.

With respect to profitability, one in three respondents reported that their business was not currently profitable. This was

unchanged for all of these from before the SSAS application. Two-thirds of the respondents reported that their businesses are

currently profitable. Of these, nine said that they were also profitable before they made the application. Four of the respondents

who indicated that their business was now profitable expressed that it was not profitable before the application. The fifth

indicated that they had not started operating when they made their application. Thus, there seems to be some evidence that

the SSAS support coincided with businesses becoming profitable.

Regarding plans for expansion, 16 of the 21 respondents indicated that they currently have plans for expansion. However,

only nine of these indicated that the support they received contributed to this decision in some way. It should be noted that

reasons given for this were not always related to the expansion in exports that the incentive aims for. There were also other

indirect impacts on respondents related to experience gained and learning because of the export shows. Interestingly, one

female respondent who was not currently profitable said that she was currently planning expansion because of the shows

anyway “because being able to attend the shows made me realise how much harder I need to drive my business to make it

profitable”. Another female respondent in the textiles, clothing and leather subsector indicated that the “trade show opened

up the possibilities for me in terms of thinking what I could do”. Another said that her plans for expansion were related to the

support received as due to the experience and information received, she “became confident and learnt the standards and

guidelines”.

However, two of those who attributed plans for expansion to the incentive were the respondents who had been operating for

less than 12 months before applying for SSAS. Therefore, it is possible that their plans for expansion naturally stem from their

business operations being in the start-up phase. It is also possible that they find great value and learning from the experience

provided by the SSAS incentive as they are still quite new in their respective industries with respect to exporting activity.

Of the four respondents who indicated their businesses had become profitable since the SSAS application, all four said that

they had plans for expansion and that this directly arose from the support they received. This suggests that the SSAS support

received was a factor in achieving profitability. Two of these respondents were male (in agro-processing and textiles, clothing

and leather) while two were female (in metals and textiles, clothing and leather).

Summing up, with respect to the direct channel of achieving greater exports, sixteen firms obtained leads through the show

and eleven firms managed to achieve increased export sales through the export show. For both men and women, around

eighty percent of respondents achieved leads, while around half of the sampled respondents achieved sales from these leads.

Of these, ten reported the value of sales achieved through the show. While most of these were under R15 000, for three

businesses in particular the value of sales achieved was substantial. All three of these obtained sales greater than R50 000

directly through the show, and all three of these were in textiles, clothing and leather. Two of these businesses were owned by

women. This suggests that the export show has been perhaps most impactful (at least in terms of direct impact) for textiles,

clothing and leather and also that women in this subsector have been able to achieve substantial exports through the shows.

Regarding the indirect channel, we cannot link the change in export performance observed directly to the SSAS support

received as many other factors could have affected export performance over the period. Nevertheless, five of the 21

respondents reported an increase in their export sales as a proportion of total turnover between their application and in the

most recent year. This suggests that even some of those who reported export sales through the direct channel were unable

to sustain increased exports after the show as eleven respondents reported sales through the show but only five firms have

been able to achieve increased overall export performance. Four of these were female (out of 16 females) and one was male

(out of five male respondents). Just under twenty percent of the respondents who received the SSAS support thus have seen

longer-term increases in their exports.



With respect to turnover, all but one of the firms saw increased turnover after receiving the SSAS support. Still it is unlikely that

SSAS is the driving force behind this as the incentive focuses on increasing exports primarily and the evidence regarding this

specific outcome, as noted above, has not been strong for the sample. It is thus unlikely that the secondary impact on turnover

would be strong as well. However, nine of the respondents indicated that the support they received contributed to their

decision to expand in some way. Further, all of the four respondents, who indicated that their business had become profitable

since the application, said that they had plans for expansion and that this directly arose from the support they received.

employment

In addition to exports and turnover we also wanted to analyse whether women benefited from the incentive through increased

employment. Figure 35 shows the total number of workers employed by the sampled firms before and after attending at least

one export show. Of the 21 firms, 11 indicated that the number of employees increased since attending the show and there

were no employment changes for the other firms. Of the firms that saw increases in employment, 90 percent are female-

owned.

However, it is still important to determine the extent to which the SSAS scheme is the source of the rise in employment. Of

the 11 firms that increased employment, five explicitly mentioned that this change was not a direct result of the SSAS. Indeed,

there are many factors, direct or indirect, that could have contributed to a firm’s employment growth.

figure 35. number of employees before and after participation in the ssas

10

7

60

50

4

4

4

4

10

10

8

8

73

50

2323

62

64

3122

00

66

42

556

328

600

133

0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70

Firm 18

Firm 16

Firm 12

Firm 11

Firm 09

Firm 08

Firm 21

Firm 20

Firm 19

Firm 17

Firm 15

Firm 14

Firm 13

Firm 10

Firm 07

Firm 06

Firm 05

Firm 04

Firm 03

Firm 02

Firm 01

Male Female

Pre-SSASPost-SSAS

Time period

Number of employees


Notes: Firms 02 and 10 both report no employment besides the business owner.

Reviewing the firms’ change in export trade before and after the export exhibition could generate some insights. The hypothesis

here is that an increase in exports leads to an increase in demand for product locally and in export markets, thereby leading

to an increase in employment. Five of the 21 sampled firms saw an increase in export share post-SSAS support, while nine

indicated that there was no change in their export share. The remaining seven respondents could not provide the change in

export share. Of the five respondents that saw an increase in export share, four were females and one was male. This suggest

that SSAS could have attributed to the firms increased export shares, where five of the firms reported increase in employment.


Figure 36 shows the number of employees pre- and post-SSAS support by gender. Two-thirds of the sampled firms stated

that the number of male employees remain unchanged during the pre- and post SSAS support period. There are six firms that

hired at least one additional male employee after attending the export show. These firms are located in agro-processing and

in chemical industries, subsectors that we had earlier described as having a higher male-to-female employment ratios. In 2016,

nearly three-fifths of employment in the agro-processing and chemical sectors was male (refer to Table A 2 in the appendix).

In contrast, 11 firms reported an increase in the number of female employees post-SSAS support while the remaining ten firms

stated that the number of female employees remained unchanged. The 11 firms that experienced growth are evenly spread

across the four subsectors under analysis: three firms each in agro-processing, textiles, clothing and leather, and chemical

industries, and two firms in metals. This is encouraging as it is evidence of positive gender shifts in the male-dominated

agro-processing and chemical industries. Despite this, seven firms that had increased their employment of women did not

specify whether it was a direct result of the SSAS support, while four firms reported that, although there was an increase in the

number of women employed post-SSAS support, this was not due to the scheme.

figure 36. number of employees pre- and post-ssas participation, by gender

0

10

20

30

40

50

60

70

Firm

02 - F

Firm

10 - F

Firm

13 - F

Firm

14 - F

Firm

06 - F

Firm

11 - M

Firm

12 - M

Firm

05 - F

Firm

20 - F

Firm

04 - F

Firm

07 - F

Firm

15 - F

Firm

17 - F

Firm

21 - F

Firm

08 - M

Firm

09 - M

Firm

18 - M

Firm

01 - F

Firm

19 - F

Firm

03 - F

Firm

16 - M

Firm

02 - F

Firm

10 - F

Firm

13 - F

Firm

14 - F

Firm

06 - F

Firm

11 - M

Firm

12 - M

Firm

05 - F

Firm

20 - F

Firm

04 - F

Firm

07 - F

Firm

15 - F

Firm

17 - F

Firm

21 - F

Firm

08 - M

Firm

09 - M

Firm

18 - M

Firm

01 - F

Firm

19 - F

Firm

03 - F

Firm

16 - M

Pre-SSAS participation Post-SSAS participation

MaleFemale

Gender

Numb

er of

emplo

yees


Notes: Firms 02 and 10 both report no employment besides the business owner.

Youth employment

A factor that we expected to influence firm hiring behaviour over the period was the Employment Tax Incentive (ETI). This is a

government tax incentive targeted at employers to encourage them to hire less experienced and young workseekers through

cost-sharing models with government (SARS, 2018). However, almost all the firms sampled indicated that they do not use the

ETI. In addition, two firms indicated that they were not aware of the incentive. While this is concerning and may be the result

of the lack of promotion or awareness of this specific support available for SMMEs, it does mean that we can be certain that

any employment shifts in this period are not attributable to the ETI.

Despite this, more young people were employed post-SSAS support. There are eight firms that employed more youth after

attending the export mission, seven of which are female-owned. Indeed, six female-owned firms employed only youth

employees.



Conditions and Quality of employment

Most firms hire workers on a temporary basis. There are 13 firms that hire temporary workers and only 6 that do not; the

remaining two did not provide a response. Of the 13 firms, eight are female-owned and owned by non-youth. Firms that hire

temporary workers are mainly located in agro-processing, textiles, clothing and leather and chemical industries.

Meanwhile, ten firms increased the number of employees working on a full-time basis. These firms are spread across all four

sectors but are predominantly located in chemical industries and textiles, clothing and leather. However, three firms had fewer

employees working on a full-time basis after the SSAS support, two of which are female-owned. Furthermore, there were no

changes in the share of full-time employees for eight firms owned by individuals characterised as non-youth. In contrast, there

are five firms which increased the number of part-time workers, 80 percent of which are female-owned.

A significant number of workers are classified as unskilled based on their type of job and education attainment levels. Pre-SSAS

support there were seven firms that had more unskilled workers than skilled or semi-skilled workers; the number increased to

nine firms post-SSAS support. The South African economy is largely services-driven, and the labour market is biased towards

highly skilled individuals, with low prospects of employment opportunities for low-skilled workers (Cassim and Oosthuizen,

2014). In the second quarter of 2018, the unemployment rate for those with a primary or lower education qualification (40.0

percent) was above the national unemployment rate (37.1 percent) (own calculations, StatsSA QLFS 2018Q2). The rise in the

number of firms in our sample that hired unskilled workers suggests that a benefit of SSAS support is a positive contribution

to jobs created amongst less skilled workers.

In summary, it is apparent that women as business owners have the potential to contribute to employment growth and

therefore economic growth: 90 percent of the firms with increased employment are female-owned. Five firms which saw an

increase in export post-SSAS were able to increase employment and, of these, three were female-owned. This might mean

that an expanded export market will result in increased demand for products, resulting in increased output and thereby

leading to a rise in employment.

broad impact of the ssas on Women

In addition, we wanted to explore whether the incentive had any impact on other women besides the female business owners and their employees. When asked how women had benefitted from the support received, 11 respondents did not provide an answer to the question, suggesting perhaps that they did not feel strongly that women have benefitted from the support received or that they could not say. An equal number of respondents felt that women benefited from the support received as did those who felt they did not benefit. None of the male respondents indicated that women had benefited from the support, either through answering “there was no benefit” (three firms) or not answering the question (two firms). These results make it difficult to draw any specific conclusions of the overall impact of SSAS support.

We also asked whether women had benefited from the incentive either through increased procurement from women-owned businesses or partnerships formed with other women following the SSAS support. Nine respondents indicated that their business had not concluded any partnerships or procured from more women-owned businesses since accessing the incentive. Four female-owned businesses indicated that they had either worked with or procured from woman-owned business since the application. However, two of these business owners stated that this was not because of the SSAS support received. One indicated that this was through the Agribusiness Development Agency (ADA), an agency in KwaZulu-Natal that aims inter alia to empower women in the agribusiness sector, and support emerging and young farmers (ADA, 2018). The other respondent did not give specific details about the woman-owned business they either worked with or procured from. The remaining eight respondents did not respond to this question.

We also hoped to find out how procurement from women-owned businesses, black-owned businesses and SMMEs had changed from before the application and after the support was received in the most recent year. Unfortunately, we did not receive many specific responses to this question: only one-third of the respondents answered this question. The overall sense and lack of response seems to indicate that respondents did not see any noticeable change in this item following the event.


We can thus not be certain that there has been any impact on the most disadvantaged groups through procurement either through new contacts or greater turnover that resulted from the event. This may suggest that a possible way of empowering vulnerable groups indirectly through such incentives is not being utilised.

Overall then, based on our analysis of responses received from a sample of 21 SSAS beneficiaries, the following findings relating to the impact of the incentive are observed:

1. Both male and female respondents express positive sentiment towards the SSAS. With respect to these respondents,

it was suggested that the positive impact of the incentive could be seen in three key areas: exposure, networking and

learning.

2. In our attempt to measure the impact of the SSAS support on the businesses’ export performance, we found that only

five of the 21 respondents reported an increase in their export sales as a proportion of total turnover, four of whom

were female. As to whether this improved export performance directly arose from SSAS support, ten respondents

(including the five female respondents) indicated that they had obtained at least one sale out of the export mission

they attended. However, we cannot say with certainty that the SSAS support was the main reason for the improved

export outcomes observed, as many factors may have contributed to the outcomes observed.

3. In addition to this, the fact that more than half of respondents reported export sales as a direct result of the show

but only around one-fifth reported better export performance in the most recent year in comparison to when they

applied suggests that, even if the incentive is having a direct effect on exports achieved through the show, this is not

being translated into longer term improved export performance.

4. Export outcomes for the sample of firms suggest that an export marketing plan may be important for achieving

greater exports through the incentive. Other marketing materials such as brochures and samples that can be improved

through the incentive may also possibly be an avenue through which the incentive can lead to export sales. However,

evidence for this was limited.

5. Regarding the overall impact of the incentive on financial performance and profitability, one in three respondents

reported that their business was not currently profitable. This remained unchanged from the situation prior to making

the SSAS application. Of the fourteen who reported that their business was currently profitable, nine said that they

were also profitable before they made the application. Thus, only five firms saw a positive shift in their profitability

from the pre-SSAS period to the post-SSAS period. Four of the respondents who indicated that their business was now

profitable also indicated that it was not profitable prior to the application.

6. Regarding plans for expansion, sixteen of 21 respondents indicated that they currently have plans for expansion. Nine

of these indicated that the support they received contributed to this decision in some way.

7. Regarding the impact of the incentive on the employment of women, 11 firms reported an increase in the number

of female employees in the most recent period after attending an export show. While some of these also reported an

increase in exports, these employment changes cannot necessarily be tied to the SSAS support received.

8. Perceptions regarding how the incentive benefits women specifically were mixed.

9. Impact in terms of greater procurement from women seems to be limited, suggesting a further channel through

which women can be empowered through such incentives that is not currently being used to its full potential.

Finally, it should reiterated that we cannot necessarily attribute all (or indeed any) of these outcomes to the SSAS incentive

as many different factors contribute to changes in variables such as exports and turnover. We are therefore unable to isolate

the effect of the incentive on turnover, especially where this was not explicitly tracked by the businesses. This re-emphasises

that, for assessment purposes, the relevant data should be collected from beneficiaries throughout the process so that

robust conclusions can be reached about whether the programme is resulting in the intended outcomes and whether these

outcomes differ for different groups.



7. finDings

7.1. main findings

7.1.1. gender Dynamics within the broader labour market

finding 1. There are important gender differences in the south african labour market

a. Men form the majority of those with better labour market outcomes (employment as opposed to unemployment) and

women dominate amongst those with worse labour market outcomes (non-searching unemployment as opposed to

narrow unemployment).

b. Participation of both men and women in the labour market is low relative to other developing countries. However,

participation of women in the labour market is lower than that of men.

c. While unemployment rates are higher for women than for men, the pattern across covariates in the same.

Unemployment rates for both men and women are highest amongst African and Coloureds, and lowest amongst

Asians and Whites; they are highest amongst the youth and lowest amongst the oldest working-age cohorts; they are

highest amongst those with lower levels of education, and lowest amongst those with tertiary qualifications; and they

are lower in urban than in rural areas.

d. Gender differences extend beyond high-level labour market outcomes and are observable in various areas of

employment. Female employment is concentrated in four industries: community, social and personal (CSP) services;

wholesale and retail trade; private households; and finance. Women dominate employment in only two industries:

CSP services, which includes government, and private households, which is primarily domestic work. In contrast,

construction, mining and transport are heavily male dominated.

e. Males are more likely than females to be employed in the formal sector and in the informal sector. In contrast, private

households account for 14.3 percent of female employment, more than four times the share for males.

finding 2. among women themselves however, there are also important differences in the labour market.

a. By race, labour force participation rates are more varied for women than for men. The labour force participation gap

between men and women is highest for Whites and Asians. Participation rates for women range from 45.5 percent

amongst Asian women to 58.3 percent amongst Coloured women.

b. Women of different skills levels are distributed differently across industries. The majority of high-skilled women are

employed in CSP services and in finance and business services. Two industries—wholesale and retail trade, and CSP

services—each account for just under one-third of semi-skilled female employment. Employment of low-skilled

women is concentrated in private households, wholesale and retail trade and CSP services.

c. African women constitute a relatively large proportion of female employment in the informal sector and in private

households compared with their share of total female employment.

d. In rural areas women (as well as men) are much less likely to be economically active.

finding 3. There are important gender differences between self-employed men and women.

a. Men are more likely to be self-employed than women. However, when we consider only those in non-tax registered

enterprises, rates of self-employment for males and females are identical at just over ten percent.

b. Almost one-third of self-employed men hire other workers, compared to fewer than one in six self-employed women

suggesting that enterprises owned by women are more likely to be survivalist in nature, with low returns.


c. Female employers also tend to employ fewer people than their male counterparts. The employees that females

employ are also more likely to be unpaid than the employees of male employers.

d. Three occupational categories accounted for the majority of self-employed women in 2016: elementary occupations,

service and sales workers and managers. This suggests a lack of occupational diversity within the sector and a bias

towards less-skilled occupations, particularly when the diversity of occupations within the managerial category is

acknowledged.

e. Just over half of self-employed women are employed within wholesale and retail trade, while a further fifth fall within

CSP services. Only two other industries—finance and business services and manufacturing—account for more than

ten percent of self-employed women.

f. Access to credit and access to affordable credit are amongst the most regularly reported obstacles for growth amongst

SMME owners. Women face specific constraints in this regard. These include constraints due to traditional norms

which exclude women from accumulating assets and property, employment and income limitations, exclusions from

financial and economic decision making and adverse attitudes towards women. The lack of financial literacy of women

compared to that of men is also a major barrier that prevents women from being able to access credit in South Africa.

finding 4. among self-employed women, there are also important differences.

a. Amongst females, Whites and Africans have the highest rates of self-employment.

b. The self-employment gender gap is particularly pronounced amongst Asians and Whites.

c. Non-tax registered self-employment rates are highest amongst Africans, with African women marginally more likely

to be self-employed than African men. As a result, Africans account for almost 90 percent of self-employed women in

non-tax registered businesses.

d. The largest cohort of self-employed women has incomplete secondary education. The bias towards lower levels of

educational attainment is even clearer when we consider the sample of non-tax registered self-employed women

only. More than seven out of ten of these women has not completed matric.

finding 5. The challenges faced by the informally self-employment differ by gender

a. According to 2013 SESE data, grants of any type are extremely rare, with less than one percent of the self-employed

reporting accessing a grant as their main source of funding – suggesting a limited reach of government programmes

and funding within the informal sector of the economy.

b. According to the SESE data, around two-fifths of the self-employed reported not needing money to start their

businesses. Close to half of those who did need money to start their businesses reported using their own money. Just

over one-tenth obtained a loan. There were no discernible differences between men and women in this regard.

c. Men were more likely to indicate that wage employment was the primary source of the money they used to start their

business. For women, the most commonly cited source of money used was from savings.

d. This suggests that government incentives are not being accessed by those in the informal sector. While this makes

sense, given that registration is often a pre-requisite to access such incentives, it is concerning as a substantial number

of individuals in need of such assistance are not able to access it.

Taken together, findings one to five suggest that incentives to increase participation in the economy cannot be gender-neutral or

gender-blind. Further, the differences noted between women suggests that there should be a specific targeting of women who are

most vulnerable rather than just all women in general. For SMMEs in particular, the nature and extent of challenges experienced differ

by gender and suggest again that gender needs to be taken into account when designing incentives so that specific challenges faced

by women in comparison to men can be addressed in a more explicit manner.



7.1.2. incentive Programmes as a Policy instrument

finding 6. south africa can learn ways in which to best support entrepreneurs from international incentive schemes.

a. It is important to match potential beneficiaries correctly to the incentive that would best meet their own business

needs.

b. Where funds are awarded, it is important to ensure that the values granted and the length of the support are

commensurate with businesses’ needs, as well as the broader growth objectives envisioned by the programme. This is

key to the overall sustainability of both the financing institution and the recipient firm

c. Efforts should be made to ensure that marginalised groups are able to access initiatives intended for their empowerment.

This may mean supporting the facilitation of the process of enterprise formalisation, where appropriate.

d. It is important to consider a set of incentives that are specifically designated for female entrepreneurs which will

attract and retain females, thus increasing overall participation and lowering poverty and inequality. This will enable

national policy agendas to have a greater impact on the individuals most in need of assistance. This necessitates a

well-coordinated policy strategy, with collaboration across different government departments, levels of government

and relevant external organisations. Such a coordinated approach is vital in the South African context, given the

various interlinked challenges to women’s full participation in the economy that fall within the mandates of a number

of different ministries.

finding 7. How the iDaD incentive schemes support individuals across provinces

a. During the 2016/17 financial year, three provinces—Gauteng, Kwa-Zulu Natal and the Western Cape—accounted for

the lion’s share of incentive approvals and approved value. These three provinces accounted for approximately nine

out of ten (88.8 percent) approved projects. These provinces include the five largest of South Africa’s eight metropolitan

municipalities, which are home to large populations and generate a disproportionately large share of total economic

output – and it is thus concerning that other provinces do not seem to be accessing the incentives in greater numbers

as investment in these more developed provinces rather than the rest of the country may serve to reinforce existing

geographical patterns of inequality.

b. It is not only the number of approvals that vary across provinces. Project values, as well as their projected additional

investments and jobs vary across provinces as well.

c. By average value, projects in Free State were relatively high value on average, while those in the Western Cape were

of relatively low value on average.

d. The projected investment ratio, defined as the ratio between the total estimated value of the additional investment

leveraged through IDAD incentives and the total value of these incentives, was highest for the Northern Cape, with

each R1 of IDAD incentives linked to R6.80 in additional investment. The Northern Cape is followed by the Free State

and Limpopo (both at a ratio of 4.2:1). In contrast, the ratio in Mpumalanga is just 0.4:1, meaning that each R1 of IDAD

incentives is linked to additional investment of R0.40.

e. On the metric of projected incentive cost per new job, the Northern Cape once again ranks highly with a cost of

R0.3 million per projected new job. The only province where this cost is lower is the Western Cape (R0.2 million per

projected new job), while in Gauteng the cost is R0.5 million per projected new job. The two provinces with the

highest cost per projected new job are Limpopo (R2.4 million) and the Eastern Cape (R1.9 million).

finding 8. How the iDaD incentive schemes support women

a. While IDAD administers and manages a number of incentive schemes targeting different enterprises, these are not

targeted to women in particular.


b. Data related to female beneficiaries in particular does not appear to be collected for any of the incentive schemes apart

from Business Process Services (BPS) under the Services Investment cluster; and Export Marketing and Investment

Assistance (EMIA) and the Sector-Specific Assistance Programme (SSAS) under the Competitiveness Investment

cluster. For each of these, there is considerable support for women despite these not targeting women in particular.

c. The number of female jobs supported in the BPS sector exceeds the number of male jobs supported. The BPS

supported 44 897 of the total IDAD jobs in 2016/17 of which women account for close to three-fifths. The share of

projects approved under this scheme was however only 0.7 percent of total IDAD approved projects, but accounts for

an estimated R7.1 billion in export revenue in 2017.

d. The largest number of EMIA approvals have been have been to male-owned SMMEs. For the full four-year period,

male-owned SMMEs account for 53.9 percent of approvals and 56.5 percent of total project value. There is however

greater support for women among approvals for firms owned by Historically Disadvantaged Individuals (HDIs). Of the

EMIA approvals in 2014/15, 56.1 percent of approvals were awarded to HDI firms and close to three-quarters of these

firms were owned by women. The share of HDI approvals however reduced to 21.8 percent by 2016/17. The share

of women owned businesses among HDI firms then rose to about four out of five in 2016/17. Thus, amongst HDI

SMMEs covered by EMIA, there is a large representation of women. It should be noted, however, that HDIs in 2016/17

comprise little more than one-fifth of all incentives awarded by EMIA, indicating room for further improvement of

SMME coverage.

e. For SSAS, female-owned SMMEs have received a larger share of approvals for all years but one (in 2016/17 where male-

owned SMMEs accounted for 56 percent of approvals). In 2016/17, 70 percent of all approvals were in three subsectors,

namely creative industries (over two-fifths); textiles, clothing and leather; and agro-processing. Approvals made in

each of the subsectors, except chemical industries and metals, were dominated by male-owned SMMEs. Roughly

three-fifths of approved projects in these two subsectors were for female-owned SMMEs.

finding 9. in addition to the dti incentive schemes, there are programmes which specifically target women to facilitate their participation in the mainstream economy. However, these programmes are very small in size compared with other dti interventions.

a. The Bavumile Skills Development Programme targets women who wants to pursue their own business by offering

them 20 days of training on sewing, knitting, weaving and craft (DTI, 2011). The main objective of this programme is to

advance women’s skills and expertise in arts and craft in order to produce better products (DTI, 2011). The substantial

expansion in the budget between 2015/16 and 2016/17—effectively a quadrupling of the budget—was accompanied

by a more than doubling from 300 to 700 in the number of female entrepreneurs trained.

b. The Isivande Women’s Fund (IWF) aims to enhance socio-economic development in rural, peri-urban and township

areas by empowering South African women (especially black women) through financial assistance of between R30

000 and R2 million and non-financial support (DTI, 2011; n.d). The fund is involved with enterprises that seeks finance

for start-up, for expanding existing enterprises, for franchising, for business rehabilition and for gap finance (DTI, n.d.).

The IWF supports SMMEs with women ownership of more than 50 percent of the ordinary share capital and more than

30 percent in management positions (DBSD, 2015 emb).

c. The South African Women Entrepreneurs Network (SAWEN) is a Section 21 registered company under the dti, with

the main objective to facilitate access to business resources, information and opportunities for South African women

enterpreneurs (SAWEN, 2012). This programme targets women specifically, who engage in informal income generating

activities and/or operate an SMME, or women who aspire to open a business, particularly rural based women-owned

SMMEs (SAWEN, 2012).



finding 10. High quality data should be collected to enable effective m&e of government programmes.

a. Lack of data, as well as poor quality data, places limitations on the types of evaluations and analysis which can be

conducted in respect of government programmes. This often means an inability to properly assess whether these

programmes are achieving their stated objectives and whether they are having a positive effect on the lives of the

most vulnerable South Africans in particular.

b. The costs of poor quality data are both social and economic. Lack of data and poor quality data have the potential to

affect an organisation’s reputation, affect its performance and could lead to loss of funds or revenue. In the specific

context of this project, the unavailability of good quality data means that it is not possible to undertake the proposed

quantitative gender analysis of dti incentives without collecting primary data.

7.1.3. ssas Case study

finding 11. Project coordinators are an important component of the administration of ssas support.

a. Firms wishing to participate in the SSAS incentive scheme must apply for support through a project coordinator

who acts as an intermediary between the dti and the applying firm. Project coordinators are uniquely placed in

that they are aware of the dti’s requirements and the SMMEs’ abilities and can navigate both parties’ needs. The dti

officials responsible for overseeing SSAS applications indicated to us that, in the 2017/18 financial year, they received

applications from approximately 1 500 firms. Project coordinators therefore play an integral role from a logistics angle

as they review and finalise each of these applications ensuring they meet the application standards and deadline.

Feedback on rejected applications is also provided directly to the project coordinators who then share it with each of

the applicant firms and work with them to amend their application for consideration in later rounds.

b. Project coordinators that are eligible to provide assistance to SMMEs include: Export Councils established through

application to the dti, Industry Associations, Provincial Investment and Economic Development Agencies; Business

Chambers; the Small Enterprise Development Agency (SEDA); Local municipalities; and Metropolitan councils. Based

on data provided by the dti, in the 2017/18 financial year, there were 26 project coordinators that represented 611

entities applying for the SSAS funding. The shares of approved projects per type of project coordinator are presented

in Figure 22. In the period under review, nearly half of the SSAS projects approved were applied for through industry

associations (45.3 percent), while a quarter of successful firms applied through SEDA (24.4 percent). Of the remainder,

similar proportions applied either through the export council or provincial investment and economic development

agencies.

c. The importance of different project coordinators varies across subsectors. In 2017/18 in some subsectors, such as

film and TV, mining and pharmaceuticals, all approved applications are from a single project coordinator; in other

subsectors, approvals come from a variety of project coordinators. Nine out of ten funded projects came from three

provinces, namely Gauteng (43.7 percent), the Western Cape (32.5 percent) and KwaZulu-Natal (14.5 percent).

finding 12. Women are a minority across almost all ssas-eligible subsectors.

a. Women account for a widely-varying share of employment within each of the twelve SSAS focus sectors for which

data is available in 2016. In virtually all subsectors, women are in the minority. Women account for the smallest shares

of employment in the metals, civil engineering, and automotive subsectors. The only subsector where women are in

the majority is the textiles, clothing and leather subsector.

b. Gender gaps by race across the different SSAS-eligible sectors show that there are four sectors where the gender gaps

in employment are particularly large and may need tailored sector-specific attention. These sectors are the automotive,

civil engineering, metals and capital equipment sectors. The gender gaps in employment across sectors differ based

on race, with the African, Coloured and Asian race groups showing particularly high male-to-female employment

ratios.


finding 13. The ssas application process is generally straightforward for all applicants.

a. Approximately half of respondents indicated that they had heard of the SSAS from either an investment or development

agency such as SEDA and Wesgro or from industry associations. In those few instances where firms heard of the

support from the dti directly, the respondents indicate that they were referred to other project coordinators to assist

with the application process.

b. The application process was described as being easy and straightforward due to the fact they worked with experienced

and knowledgeable project coordinators.

c. Despite overall positive sentiment, two specific challenges were raised regarding making the application. Firstly,

it was noted that the dti often provided feedback at the last minute which made it difficult for firms to plan

accordingly. Secondly, respondent firms indicated that it was quite onerous to collect and compile the accompanying

documentation.

d. One drawback of using project coordinators to facilitate the application process may be the potential for gatekeeping

(or the perception of gatekeeping). This was alluded to by one respondent, who suggested that coordinators might

choose not to assist firms in the application process or share information on upcoming opportunities if they did not

“like you or your firm”. There is no evidence, though, that this is actually happening; nevertheless, such potential issues

should be explicitly taken into account when designing application systems and processes.

finding 14. The ssas application process is similar for men and women

a. Males and females receive similar assistance and face the same application process and type of support. Despite this,

women generally constitute the majority of those that receive support from the SSAS incentive scheme, as was shown

earlier in Figure 17. Over the full 2013/14-2016/17 period, female-owned SMMEs accounted for 55.3 percent of all SSAS

approvals.

b. Male and female respondents identified similar reasons for applying for the emerging exports support, namely to grow

their export markets, to identify distribution partners and channels, and to undertake market research. In addition,

female owners identified three additional reasons. These were to seek out new marketing or display techniques from

interactions at the international trade shows; for brand exposure; and to compare the quality of products produced

locally to those produced internationally. This reveals that there may be some intrinsic differences between these

categories of owners with regards to their operating environment that might require different support.

finding 15. measures of success for the programme do not currently include gender as an aspect of consideration.

a. The dti, according to officials we spoke to, measures success according to various metrics. One measure is whether the

firm share of exports as a proportion of turnover has increased since application. Second, they consider the number

of export leads that the firm was able to convert into direct sales following the export mission. Third, whether the

firm has created employment following the export mission(s) is considered. Fourth, financial growth is an important

marker. Here the dti is concerned with whether overall turnover has grown post-SSAS support. Fifth, some of the firms

that are supported did not have marketing or advertising material prior to receiving support; after the export mission,

they often have samples, marketing brochures and experience with setting up stands at these trade shows. Post-

support they have gained this vital experience as well as the actual samples that they can use in further domestic and

international marketing activities. Gender is however not considered in any of these metrics.

b. According to dti officials, detailed information on the impact of SSAS is collected by the dti’s monitoring and evaluation

team who often prepare success stories on SSAS recipients as well as provide input into the IDAD’S Annual Incentive

Report. Twice a year, the SSAS team prepare a report on how disbursed funds were spent and the characteristics of

supported firms. Further, the project coordinators also collect any information on the impact of SSAS support to the

recipient firms. We were unfortunately unable to access any of this data and analysis.



finding 16. The support received from both the dti was indicated to be sufficient by most respondents.

a. The support received from the dti was indicated to be sufficient by seventeen of the twenty-one respondents. Of

the four who indicated that the support was not sufficient, three female respondents indicated that markets are

different across the world and that the scheme is not designed to let them tap into their target market, or assist with

the distribution of goods across the world or locally. One respondent felt that he had to do “everything himself”. These

concerns may indicate a mismatch between expectations and what the SSAS is designed to do, but also provide

feedback that may be used to improve the experience of beneficiaries.

b. In response to whether firms would require further dti support, four respondents (three females and one male) indicated

that they would like assistance with market research or marketing tools. Another female respondent indicated that

she would like assistance with understanding tax, excise duties and customs better. Six respondents, four of whom

were male, indicated that they would like assistance to procure machinery (capital) to stimulate production for both

local and international markets, and skills training for their staff. This suggests that a large proportion of the men

interviewed view capital as a constraint to their business and as a barrier to growing export production.

finding 17. support received from project coordinators was indicated to be mostly sufficient. There were however suggestions of additional support that would be beneficial.

a. Eight respondents stated that they received no support from the project coordinator. Of these, half were female.

It is unclear as to whether these respondents requested support and did not receive it, or if support was simply

unavailable to them.

b. Six respondents indicated that they received active support. This took the form of guidance on how to improve

local sales and how to use foreign contact to improve their business, the importance of marketing tools such as

catalogues, and key requirements for trade shows. This was in addition to courses run on various aspects of small

business development.

c. The input from respondents on the ways in which project coordinators could improve the support provided varies

across the four sectors, but relates to three common themes: preparation for the export show with a focus on

networking and marketing, capacity building workshops that touch on various aspects of business development and

management, and more financial support. This latter support however is out of the scope of what can be provided by

the project coordinator.

finding 18. There were varying perceptions of the barriers that exist to female entrepreneurs in establishing successful businesses.

a. While SSAS support is sufficient in that it fully covers the cost of participating in international trade missions, as an

incentive that seeks to foster industry- or sector-wide development the quality of support offered is lacking because

it fails to fully address the issues faced by businesses within the sector that will limit their ability to grow export

production.

b. In the metals subsector, most respondents were female and working as jewellery designers and producer. Respondents

indicated that access to markets and finance posed a key challenge. More specifically, knowledge relating to basic

business administration seems to be a challenge for female respondents, particularly around providing quotes and

invoicing. With regards to finances, the respondents cited the high start-up costs associated with setting up jewellery

production as limiting entry into the sector.

c. In agro-processing the challenges for female entrepreneurs seem more prominent. The industry is male-dominated

and female respondents indicated that it was very difficult for female entrepreneurs to access funding. There also

seems to be an unwillingness or reluctance from men in the industry to engage with female entrepreneurs, making it

challenging for women to partner with men to finalise deals


d. In the female-dominated textiles, clothing and leather subsector, respondents highlighted a lack of marketing skills as

a challenge. Female respondents also note that they are not taken as seriously as men in business related matters with

the result that they often work harder to be considered credible.

e. In the chemicals industries, female respondents said that the barriers faced by women seem to be no different from

the barriers faced by men and include a lack of funding and difficulty in penetrating markets. In this subsector there

also seems to be high operating costs which act as a barrier to women who struggle to access funding.

f. Respondents suggested support to encourage greater female participation including promoting greater awareness

of dti incentives, organising workshops for small business owners on various topics, encouraging greater access to

funding as well as mentorship and business coaching.

finding 19. While the impact of the ssas may be through many channels, improvements cannot necessarily be tied to the ssas.

a. Firm turnover might have been affected in two possible ways by SSAS: first, through the direct channel of export

markets accessed through the export shows, and second through the improved product and business processes as

well as contacts made because of the export shows.

b. While only five of the companies interviewed experienced an increase in their export sales as a proportion of total

turnover, eleven respondents (including five female respondents) indicated that they had obtained at least one sale

out of the export mission they attended. Therefore, even if the incentive is having a direct effect on exports achieved

through the show, this might not yet be translated into longer term improved export performance.

c. An export marketing plan may be important for achieving greater exports through the incentive. Other marketing

materials such as brochures and samples that can be improved through the incentive may also possibly be an avenue

through which the incentive can lead to export sales.

d. All but one of the firm saw increased turnover after receiving the SSAS support. While this cannot be directly linked to

the SSAS support, it is clear that SSAS is well-targeted at growing rather than declining firms.

e. While one-third of respondents reported that their business was not currently profitable, five firms saw a positive shift

in their profitability from the pre-SSAS period to the post-SSAS period.

f. Three-quarter of the firms planned to expand and more than half of these firms indicated that the SSAS support they

received contributed to this decision.

g. Experience and learning can be impactful, if harder to measure. Female respondents indicated that the trade shows

had: opened up possibilities in terms of their thinking on what was possible; shown them that they needed to drive

their business harder to make it profitable; and given them confidence through the experience received.

h. Around half of firms reported an increase in the number of female employees in the most recent period after attending

an export show, although these employment changes cannot necessarily be tied to the SSAS support received.

i. Perceptions regarding how the incentive benefits women specifically were mixed. Only ten respondents provided a

response when asked if women had benefitted from the SSAS support received. An equal number of these felt that

women benefited from the support received as did those who felt they did not benefit.

j. Impact in terms of greater procurement from female-owned businesses appeared to be limited, suggesting a further

channel through which women can be empowered through such incentives that is not currently being used to its full

potential.



7.2. incorporating Considerations of gender into gender-blind incentive schemes

Gender can be incorporated into existing gender-blind incentive schemes in two ways: first, by explicitly targeting women

and outcomes related to their empowerment within the theory of change; and, secondly, by considering whether men and

women respond differently to various aspects of the intervention in terms of their behaviour and making appropriate design

adjustments. However, where neither option is appropriate, for whatever reason, a further available course of action is to

design a new, targeted programme.

The first option requires an explicit acknowledgement of women within the goals of the incentive. Practically, in terms of

measurable outcome, this means that we are interested in the following SSAS outcomes as they relate to women:

i. Increasing the share of exports sold by women-owned businesses; and

ii. Increasing the turnover of women-owned businesses so that as their businesses grow, they can in turn employ more

individuals (both male and female) and procure from other SMMEs including those that are female-owned and run.

The second option requires an understanding of each step along the process of accessing and benefiting from the SSAS

support. This is helpful as it enables us to collect the necessary data and determine whether there are behavioural differences

between men and women, as well as how different applicants are treated within the process by the relevant authorities, such

as the dti and project coordinators. This requires a systematic consideration of each step of the process and how men and

women experience these. We do this below using the responses to our questionnaire and our understanding of how the

process is carried out (see Figure 26).

awareness of the incentive

Here, it is important to consider from a gendered perspective whether women are aware of the incentive and are therefore able

to access it. A recommendation with respect to this initial stage of the process is to check the modes via which beneficiaries

learn about this incentive and whether women have equal and ready access to each of these sources. We understand that

most, if not all, beneficiaries become aware of SSAS from a development agency or industry association that also then serves

as their project coordinator. We did not have access to membership details of all the project coordinating organisations in

order to compare the gender profiles against those of applicant firms in order to determine whether there seemed to be any

exclusion in terms of awareness of the SSAS incentive.

We did receive some feedback from our sample of beneficiaries regarding how to encourage female owned businesses to

seek support from the dti. The common themes included an effort to increase awareness and knowledge about what kind

of support is available, with focus on successful case studies of women who have received support made available to other

applicants. Respondents also noted that while a lot of support is available from the dti, they often lack awareness of such

initiatives. A remedy to this would be to undertake a roadshow, particularly targeted at female entrepreneurs. These responses

indicate the respondents’ view that more could be done so that women can access the relevant dti incentives.

application Through Project Coordinators

At this stage, it should be considered whether men and women experience any differences in their application. The responses

to our questionnaire suggest that there were no noticeable differences in the way male and female applicants experience the

process as the SSAS incentive lacks an inbuilt mechanism to distinguish between the two categories of applicants. Both groups

of applicants heard of the incentive through similar channels and used the project coordinators to finalise their applications.

Additionally, both sets of applicants found the guidelines and application process easy and straightforward.

However, three female respondents raised specific issues. These related to the length of time that it took to put together the

compliance documentation and the fact that the dti often finalises application outcomes too late for some firms to undertake


the necessary arrangements. These however are generic administration issues and do not seem to be suggestive of any

specific problems that may be experienced by females in comparison to males.

When asked for their reason for applying for the emerging exports support, male and female respondents cited similar reasons.

These included growing their export markets, identifying international distributional channels and undertaking research to

understand what is required to begin exporting to foreign markers. Some female owners however also indicated the desire to

seek out new marketing or display techniques and to compare the quality of their products to those produced internationally.

Therefore, there seems to be at the application stage a suggestion that there may be some difference between what men and

women are hoping to achieve from the process and incentive, but no actual difference in how they experience the application

process itself.

Critically, however, due to the requirements of the SSAS that applicants are expected to meet, a significant portion of female

entrepreneurs are likely to be excluded. Specifically, no informal sector firm is able to qualify for support. This is particularly

problematic from the perspective of addressing gender- and race-linked economic disadvantages.

application outcome

At this stage, we need to consider whether gender is considered by the dti when it makes its final decision. Bearing in mind

that most applications are submitted through a project coordinator who reviews and finalises the applications, it is unlikely

that gender plays a specific role at this process. What seems to be more important is that women are aware of the incentive

and apply through the project coordinator to benefit from the incentive.

event Preparation and Disbursement of funds

Here, we must consider whether women are likely to require a particular type of support from the project coordinator, as well

as whether there may be any difference in the treatment of men and women in how they access support from the project

coordinator.

Across both men and women however, of the 21 respondents in our sample, eight indicated that they received no support

from the project coordinator - four men and four women. This is concerning as support from the project coordinator (at any

point during the process) is one mechanism through which the outcomes from the incentives can be maximised.

Of the six respondents who indicated they received active support, five of these were women. The support received took the

form of guidance on how to improve local sales and make use of contacts received through the initiative for the improvement

of business, the importance of the use of catalogues and what is needed for trade shows, and courses run on aspects of small

business development. Female respondents thus seemed to be more satisfied with the support received from the project

coordinators. This could be due to them demanding and making use of the support offered by the project coordinators, in

comparison to men who seemed to not be as interested in the type of skills and guidance support that could be received

through the project coordinators. Men seemed to rather emphasise the funding aspect of the support received in responses

to our questions regarding support received.

This was also the case when we asked respondents about how project coordinators could improve the support provided.

Women again seemed to be more likely to emphasise that preparation and marketing support could be improved. Twelve of

the sixteen female respondents and four of the five male respondents indicated that the assistance provided by the dti was

sufficient across the entire process, again not highlighting any particular difference between men and women in this regard.

These results are suggestive of women requiring support before the show so that they can derive the maximum benefit from

the experience. This, however, does not preclude men from this type of support as well - and indeed, given the small sample



of men, we cannot say definitively that they do not require this support as well. What it does suggest however is that such

preparation support seems to be vitally important for women in particular, and project coordinators (and any other relevant

stakeholders) should ensure that women are able to access the necessary support before attending the show.

With particular reference to preparation for the show, four of the respondents (three females and one male) indicated that

they would like assistance with market research or marketing tools. One female respondent indicated that they would like

assistance with understanding tax, excise duties and customs better. Another female respondent indicated that they would

like business management advice and business development support, this would include tips on how to follow up on leads

received at conventions.

With specific reference to the event and follow-up after the event, one female respondent stated that they found it difficult

to finalise and close deals. Particularly, respondents indicated that assistance in implementing networking skills are needed at

trade shows since entrepreneurs are constrained by having to man their stations. Respondents also indicated that they would

like advice on how to best proceed after the show, in terms of following up on leads and contacts. This type of guidance could

be provided to beneficiaries before they attend the export mission.

Regarding those who indicated that the support was not sufficient, three female respondents made specific reference to the

nature of the programme indicating that markets are different across the world and the incentive scheme is not designed to

let them tap into their target market or assist with the distribution of goods across the world or locally; suggesting that they

felt the event and support should be better catered to them. One female respondent indicated specifically that the export

programme, in their opinion, is suited to bigger, more well-established businesses who are capable of exporting regardless of

government intervention. That is, it is not designed or tailored for smaller businesses.

Overall, regarding assistance they would like to receive (not only from the project coordinator but from the dti directly as well),

the results are suggestive of men being more likely to require and ask for assistance with regard to funding alone rather than

skills and training for themselves in comparison to women, suggesting that the key constraint for them is more likely to be

related to funding concerns only. Women, on the other hand, seem to be more likely to ask for assistance with respect to their

own knowledge and skills, suggesting that training and workshops could be important for this group.

event

At the event, we would want to know whether women and men differ in any of the aspects that we hypothesise will lead to

increased exports and turnover: that is, obtaining leads, contacts and learning gained from the event.

In this regard, in our sample, nine of the sixteen sampled women and three of five male respondents indicated exposure as a

major way in which they benefited from the programmes, suggesting this type of benefit for both men and women.

Regarding networking, women were more likely to indicate this as an area in which they benefited from the SSAS. Three female

respondents explicitly cited this as a channel through which they benefited when we asked how beneficiaries benefited from

the event. None of the five men in the sample however mentioned this as a key area in which the SSAS support had an impact

on their business, suggesting possibly that women stand to gain more from the contacts and networks that can be formed

through such events. We would however hesitate to make a definitive conclusion on this given the small number of men in

the sample.

Four of the sixteen women in our sample indicated a great impact through learning from the experience and being able to

refine their products. Three of the five men indicated a positive impact through learning about their product and the market.

This again suggests that this is an important area in which businesses can benefit from SSAS for both men and women.


Post-event observed outcomes

Outcomes should be measurable at the aggregate level and specifically for women. Practically, this means that we should be

able to disaggregate outcomes data by gender, both for the financial outcomes of businesses as well as for employment and

procurement.

A gender-sensitive incentive scheme is concerned not only with increasing the exports and turnover of all small businesses,

but in increasing exports and turnover for women-owned businesses specifically so that women can grow their businesses

and be empowered. This means that the direct effect on exports and the secondary effect on domestic turnover should be

measurable for female-owned firms particularly.

Further, it would be important to consider other effects that the incentives may have on women. Regarding these “knock-on”

effects, we are interested in the following two: increase female employment and the level of procurement made from female-

owned businesses. In this regard, there may be potential for increased turnover to be linked to procurement from female-

owned businesses through an appropriate incentive to procure from such businesses or an appropriate network through

which female-owned businesses can form agreements and partnerships.

In terms of outcomes observed for our sample, it was difficult to draw any patterns of outcomes among men or women given

the small sample size of 21. This was particularly true for the secondary effects that SSAS may lead to on domestic turnover

and the knock-on effects that SSAS has the potential to have on employment and procurement.

Ten respondents (three male and seven female respondents) indicated that they had obtained at least one sale out of the

export show they attended. Comparing the pre- and post-support figures, five respondents (out of the 10 who achieved sales

from the show) reported an increase in their export sales as a proportion of total turnover. Four of these were female and only

was one male.

Given the small sample, we cannot conclude definitively whether women have been more or less successful in achieving

export sales through the show or whether they reported a higher export share as a proportion of turnover than men. It seems

that both men and women however have been able to benefit from SSAS, in the immediate term at least, with sixty percent

of the men in the sample and 44 percent of the women in the sample having achieved at least one sale from the show.

Longer term though, only five respondents have achieved increased exports as a share of total turnover and we cannot

confidently attribute this to SSAS retrospectively given that many factors may have affected this outcome. It is important to

understand the linkages between the SSAS support and export performance. Thus, it is unfortunate that we have been unable

to link export outcomes for the latest years for the sampled firms to the SSAS support received. Similarly, our results show that

turnover increased for most of the sample relative to its pre-application level, while around half of firms reported an increase

in the number of female employees or an increase in the number of African employees.



8. ConClUsion anD ReCommenDaTions

This research was commissioned by the Department of Women with the objective of reviewing the effectiveness of dti

incentives and, in particular, how women access these incentives and benefit from them. The work was undertaken over

two phases, the first of which summarised the different dti incentives but was limited by various data constraints in its ability

to compare male and female beneficiaries in a meaningful way. The second phase focussed on a single dti incentive—the

Sector-Specific Assistance Scheme (SSAS)—and interviewed a sample of beneficiaries and project coordinators to ascertain

how recipients experienced the incentive.

Based on the various findings presented in this report, we present the following recommendations:

Recommendation ia. if government is serious about properly measuring and monitoring the performance and impact of incentive schemes, the collection of relevant data must be prioritised.

Recommendation ib. Data collection for the purposes of measuring performance and impact of incentive schemes should be integrated into the design of the scheme to ensure accuracy and completeness.

Data related to female beneficiaries in particular does not appear to be collected for any of the incentive schemes apart

from Business Process Services (BPS) under the Services Investment cluster; and Export Marketing and Investment Assistance

(EMIA) and the Sector-Specific Assistance Programme (SSAS) under the Competitiveness Investment cluster. We recommend

that that, for assessment of impact on women purposes, data related to gender be collected from all beneficiaries so that

robust conclusions can be reached about whether any particular programme is resulting in positive outcomes for women in

particular.

Gender is obviously important from the perspective of this study. However, it is important that data collection not be informed

by narrow interests, but should take into account government’s broader objectives and international commitments. Thus,

other aspects such as age, race, disability status should, where feasible and appropriate, be collected as standard practice.

Further, data should be collected at various stages of the process to ensure that assessments of impact are robust. In other

words, it is crucial to have data on the pool of potential applicants, successful applicants and unsuccessful applicants.

Recommendation ii. Women’s access to incentive programmes should be prioritised in order to effectively help address their historical and continuing economic marginalisation.

Our findings indicate that there are important gender differences in the South African labour market. Women are less likely

to participate in the labour market and more likely to be unemployed than men. They are also more likely to work in private

households, CSP services and wholesale and retail trade than men. Furthermore, among women, there are also important

differences with the worst labour market outcomes being observed for African and Coloured women. This is true in respect of

those who are self-employed as well as for all those active in the labour market.

Regarding access, it is also concerning that many seem to be become aware of such incentives through industry associations

and project coordinators, as exemplified in our consideration of the SSAS incentive – this restricts access to those who are

already participating in the economy at a certain level with certain industry contacts. In industries where women are not

currently represented, this serves to reinforce the current gender structures of industries and even where they serve to

empower women, only empower the few women who have been able to succeed against odds in male-dominated industries.

Taken together, our findings noting the differences between men and women, and among women, suggest that incentives

to increase participation in the economy cannot be gender-neutral, and further, that there should be a specific targeting of

women who are most vulnerable rather than just all women in general.


Currently the dti incentives do not target women explicitly. This means that they are not formulated with the needs of women

in mind and are not aimed where women most in need of them can accessed them. To improve the access of women to dti

incentives, the dti should take into account employment and self-employment trends with specific reference for women.

Further, a particular focus on women’s access to incentives may be warranted in subsectors that are particularly male-

dominated.

Recommendation iiia. To promote women’s fuller economic participation, incentive programmes and other types of support cannot ignore those in the informal sector or those in rural areas or smaller urban centres.

Recommendation iiib. Where providing support to the informal sector is not feasible, for whatever reason, policy should focus on making formalisation both an attractive option and a relatively straightforward process.

This would entail a greater focus on women in rural areas and the self-employed women in the informal sector, most of whom

are African. It would also require a focus on enabling access for the youth and those with the lowest levels of education.

As these women are most excluded from the formal economy, failing to target these women explicitly allows patterns of

inequality to be replicated as these women also remain excluded from incentives that can serve to improve their financial

positions.

Geographically, during the 2016/17 financial year, three provinces – Gauteng, Kwa-Zulu Natal and the Western Cape –

accounted for approximately nine out of ten approved projects. These provinces include the five largest of South Africa’s

eight metropolitan municipalities, which are home to large populations and generate a disproportionately large share of

total economic output – and it is thus concerning that other provinces do not seem to be accessing the incentives in greater

numbers as investment in these more developed provinces rather than the rest of the country may serve to reinforce existing

geographical patterns of inequality.

According to 2013 SESE data, use of grants of any type are extremely rare for the self-employed, with less than one percent

of the self-employed reporting accessing a grant as their main source of funding – confirming a limited reach of government

programmes and funding within the informal sector of the economy. While this makes sense, given that registration is often a

pre-requisite to access such incentives, it remains exclusionary with a substantial number of individuals, including women, in

need of such assistance not being able to access it.

We recommend that efforts should be made to ensure that marginalised groups are able to access initiatives intended for their

empowerment. In the context of the high numbers of self-employed women in the informal sector in South Africa, this may

mean supporting the facilitation of the process of enterprise formalisation, where appropriate.

Recommendation iv. The dti should monitor impact in terms of gender as a standard feature of evaluations of their interventions.

In our consideration of the SSAS incentive, we further noted that the measures of success that are currently being used by the

dti for the programme do not currently include gender in any form. We recommend that gender indicators become a standard

component of such programmes as part of a national agenda to drive the inclusion of women into the economy. With specific

reference to SSAS, this would mean that the indicators be collected in a manner that allows the data to be disaggregated by

gender.

Generally, however, impact for women as both business owners and as employees should be assessed, although it might not

be possible or appropriate in all instances.



Recommendation v. While assessments of incentive schemes and other similar interventions are economic in nature, it is worth trying to understand their impact in terms that are not purely economic but which may in turn have important effects on outcomes.

Sixteen of 21 respondents indicated that they currently have plans for expansion and nine of these indicated that the support

they received contributed to this decision in some way. It should be noted that reasons given for this were not always related

to the expansion in exports that the incentive aims for. There were also other indirect impacts on respondents related to

experience gained and learning because of the export shows. Interestingly, one female respondent who was not currently

profitable said that she was currently planning expansion because of the shows anyway “because being able to attend the

shows made me realise how much harder I need to drive my business to make it profitable”. Another female respondent in the

textiles, clothing and leather subsector indicated that the “trade show opened up the possibilities for me in terms of thinking

what I could do”. Another said that her plans for expansion were related to the support received as due to the experience and

information received, she “became confident and learnt the standards and guidelines”.

We thus recommend that softer measures of success should be considered when measuring impact in addition to numbers

such as profits and employment. This is especially so in the short term where learning and esteem effects may be an immediate

result of participation in an incentive scheme rather than increased profits or expansion which may only occur much later as

a result of such positive effects.

Recommendation vi. The ssas may need tailoring to account for the specific challenges faced by women and women-owned firms.

Incentives may need to differ, either entirely, or in specific components to take account of specific challenges faced by

women in comparison to men. For example, we have noted that women face specific constraints with respect to access to

finance. These include constraints due to traditional norms which exclude women from accumulating assets and property,

employment and income limitations, exclusions from financial and economic decision making and adverse attitudes towards

women. The lack of financial literacy of women compared to that of men is also a major barrier that prevents women from

being able to access credit in South Africa. This finding highlights that while challenges are experienced by all SMMEs, the

nature and extent of these problems differ by gender and suggest again that gender specific needs to be taken into account

when designing incentives so that specific challenges faced by women in comparison to men can be addressed in a more

explicit manner.

With specific reference to financial challenges, it is vital to improve financial literacy for women in order to empower them to

use financial products for the promotion of entrepreneurship and other economic activities. This is summarised in a quote from

a study by the International Finance Corporation, which highlights “the need for a more deliberate and integrated strategy

focusing on women in business. Since women are the largest group of entrepreneurs in the country, gender-focused business

strategies must inform all BEE and financial access measures. Institutions which act now to better understand and service this

large, growing segment of South Africa’s business population will reap the benefit in the future” (World Bank, 2006).

When assessing the constraints to small business growth and entrepreneurship in South Africa, it is important to take into

account the extent to which these constraints disproportionately affect women. For example, while policies enhancing access

to credit are important for both the creation and growth of SMMEs, these interventions will disproportionately support men if

the gender-specific constraints to accessing finance for women are not also addressed.

In the case of our SSAS survey, there was some suggestion that women would value training and skills support from project

coordinators more than men. The incentive could thus become gender-sensitive and respond to a factor such as this by

ensuring that it emphasises the obtaining of the types of skills which were indicated to be in need by women so that can

derive maximum benefit from the incentive.


Further, based on varying barriers that exist to female entrepreneurs in establishing successful businesses across different

sectors, incentives may be tailored by sector to respond to the specific needs of women in particular industries. Incentives

such as SSAS may seem adequate in that they fully cover a stated cost i.e. the cost of participating in international trade

missions, but may ultimately be lacking because it fails to fully address the issues faced by businesses within the sector that

will limit their ability to grow. Thus, the circumstances in which female-owned businesses operate should be understood and

incentives should be designed to take account of these so that women can fully benefit from them.

Recommendation vii. south africa should remain open to learning from the experiences of other countries and adapt policy where necessary.


In line with these, it is recommended that:

i. The needs of potential beneficiaries be understood so that they can be matched to incentives that best suit their own

business needs. This might entail potential beneficiaries undergoing a needs assessment as part of the application

process so that they can be matched to an incentive that meets their needs and expectations and so that incentives

can be developed to be in line with the needs of applicants;

ii. Funds be awarded only in line with the support commensurate with the business’s needs, as well as the broader

growth objectives envisioned by the programme. This will facilitate the overall sustainability of both the financing

institution and the recipient firm;

iii. Efforts should be made to ensure that marginalised groups are able to access initiatives intended for their

empowerment. In the context of the high numbers of self-employed women in the informal sector in South Africa,

this may mean supporting the facilitation of the process of enterprise formalisation, where appropriate; and

iv. A set of incentives be developed that are specifically designated for female entrepreneurs which will attract and

retain females, thus increasing overall participation and lowering poverty and inequality. This should be done in

line with a national policy agenda to have a greater impact on the individuals most in need of assistance. This

necessitates a well-coordinated policy strategy, with collaboration across different government departments, levels

of government and relevant external organisations. Such a coordinated approach is vital in the South African context,

given the various interlinked challenges to women’s full participation in the economy that fall within the mandates

of a number of different ministries.



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aPPenDix i: DaTa

Various datasets are utilised in the analysis of the South African labour market. We rely on four key datasets namely the Quarterly

Labour Force Surveys and the Labour Market Dynamics in South Africa; the National Income Dynamics Study; and the Survey

of Employers and the Self-Employed.

The Labour Market Dynamics (LMD) data is essentially a compilation of the four Quarterly Labour Force Surveys (QLFS)

conducted by Statistics South Africa (StatsSA) in a given calendar year. The survey collects data on the labour market activities

of individuals aged 15 years or older who live in South Africa. The LMD dataset also includes certain variables (such as income)

that are collected as part of the QLFS, but which are not published in the QLFS datasets. The LMD data has been published for

each year since 2008, with the latest available data being that for 2016.

The 2013 Survey of Employers and the Self-Employed (SESE) was conducted by Statistics South Africa in the third quarter of

2013 using a sample from the Quarterly Labour Force Survey of that quarter. The main aim of the SESE is to collect data on

micro- and small businesses in South Africa, their operation and access to services; to collect income tax information on non-

VAT paying businesses; and to determine the contribution of these businesses to the economic growth of the country. SESE

is used here to further the analysis of women who are self-employed and employers, and to compare their characteristics to

men in self-employment.



Table a 1. matching of siC codes to ssas subsectors

subsector siC Codes

Agro-processing

301. Production, processing and preservation of meat, fish, fruit, vegetables, oils and fats302. Manufacture of dairy products 303. Manufacture of grain mill products, starches and starch products and prepared animal feeds304. Manufacture of other food products

Automotive 631. Sale of motor vehicles 632. Maintenance and repair of motor vehicles633. Sale of motor vehicle parts and accessories634. Sale, maintenance and repair of motor cycles and related parts and accessories

Creative industries

324. Publishing325. Printing and service activities related to printing326. Reproduction of recorded media

Chemical industries

334. Manufacture of basic chemicals 335. Manufacture of other chemical products

Metals 351. Manufacture of basic iron and steel352. Manufacture of basic precious and non-ferrous metals 353. Casting of metals 354. Manufacture of structural metal products, tanks, reservoirs and steam generators355. Manufacture of other fabricated metal products; metalwork service activities

Capital equipment

356. Manufacture of general purpose machinery357. Manufacture of special purpose machinery


882. Architectural, engineering and other technical activities

Civil engineering

501. Site preparation503. Building installation 504. Building completion(note: Building of complete constructions was left out)

Textile and clothing

311. Spinning, weaving and finishing of textiles312. Manufacture of other textiles 313. Manufacture of knitted and crochet fabrics and articles314. Manufacture of wearing apparel, except fur apparel316. Tanning and dressing of leather; manufacture of luggage and handbags317. Manufacture of footwear

Film production 961. Motion picture, radio, television and other entertainment activities

Electro-technical

361. Manufacture of electric motors, generators and transformers362. Manufacture of electricity distribution and control apparatus363. Manufacture of insulated wire and cable364. Manufacture of accumulators, primary cells and primary batteries 365. Manufacture of electric lamps and lighting equipment366. Manufacture of other electrical equipment N.E.C. 371. Manufacture of electronic valves and tubes and other electronic components 372. Manufacture of television and radio transmitters and apparatus for line telephony and line telegraphy 373. Manufacture of television and radio receivers, sound or video recording or reproducing apparatus and associated goods

ICT services 752. Telecommunication862. Software consultancy and supply


aPPenDix ii: aDDiTional figURes

figure a 1. expanded unemployment rates by gender, 2018

37.645.8

27.4 28.1

13.421.4

11.0 12.5

62.3

72.7

39.447.7

23.9

33.8

21.826.1

17.1 16.5

37.044.1 41.4

51.4

32.641.0

17.522.6

6.110.5

29.336.4

45.053.1

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

African Coloured Asian White 15-24 yrs 25-34 yrs 35-44 yrs 45-54 yrs 55-64 yrs

Primary Inc. Sec. Comp. Sec. Dipl/Cert Degree Urban Rural

Race Age

Educational Attainment Location

MaleFemale

Perce

nt

Source: StatsSA, Quarterly Labour Force Survey 2018Q2.



aPPenDix iii: aDDiTional Tables

Table a 2. Race and gender composition of employment across ssas-eligible subsectors, 2016

african Coloured asian White Total

m f m:f m f m:f m f m:f m f m:f m f m:f

Agro-processing

41.9 28.0 1.5 11.2 8.4 1.3 2.5 1.1 2.2 4.0 2.8 1.4 59.6 40.3 1.5

Automotive 56.3 5.5 10.2 7.4 1.4 5.4 8.2 0.4 18.7 16.1 4.6 3.5 88 11.9 7.4

Capital equipment

38.8 8.4 4.6 7.9 2.6 3.0 4.1 0.7 5.7 25.6 11.9 2.2 76.4 23.6 3.2

Chemical industries

46.3 17.8 2.6 4.8 6.7 0.7 3.1 1.9 1.6 7.2 12.3 0.6 61.4 38.7 1.6

Civil engineering

67.4 5.0 13.5 12.3 0.8 14.8 1.5 0.1 18.1 11.0 1.9 5.9 92.2 7.8 11.8


37.8 9.0 4.2 7.6 2.0 3.8 3.6 1.6 2.2 31.8 6.7 4.8 80.8 19.3 4.2

Creative industries

23.3 17.0 1.4 12.1 15.7 0.8 11.4 2.2 5.1 9.6 8.7 1.1 56.4 43.6 1.3

Electro-technical

44.4 16.7 2.7 9.7 5.0 2.0 0.9 2.1 0.4 15.5 5.7 2.7 70.5 29.5 2.4

Film & TV 48.7 13.8 3.5 7.8 2.5 3.2 2.4 1.6 1.5 12.3 11.0 1.1 71.2 28.9 2.5

ICT services 21.6 16.2 1.3 8.2 3.8 2.1 6.1 2.6 2.4 31.3 10.3 3.0 67.2 32.9 2.0

Metals 61.8 7.1 8.8 10.2 0.3 36.4 2.4 0.5 4.5 15.0 2.8 5.4 89.4 10.7 8.4


22.9 47.6 0.5 5.9 11.7 0.5 3.3 5.3 0.6 1.1 2.2 0.5 33.2 66.8 0.5

Source: Own calculations. StatsSA, Labour Market Dynamics, 2016

Notes: Figures are for males (M) and females (F), with the male-to-female ratio (M:F) presented for each race within each subsector. Employment shares add to 100 within each subsector.

Table a 3. female share of employment across ssas subsectors, 2013-2016

subsector 2013 2014 2015 2016 average

female share

(%)

m:f ratio

female share

(%)

m:f ratio

female share

(%)

m:f ratio

female share

(%)

m:f ratio

female share

(%)

m:f ratio

Agro-processing

36.2 1.8 35.3 1.8 41.0 1.4 40.4 1.5 38.2 1.6

Automotive 15.1 5.6 14.9 5.7 16.5 5.1 11.9 7.4 14.6 5.8

Capital equipment

12.8 6.8 20.5 3.9 21.8 3.6 23.6 3.2 19.7 4.1

Chemical industries

36.2 1.8 30.9 2.2 39.5 1.5 38.7 1.6 36.3 1.8

Civil engineering

8.1 11.4 8.6 10.6 7.1 13.1 7.8 11.9 7.9 11.7


21.0 3.8 22.6 3.4 20.0 4.0 19.2 4.2 20.7 3.8

Creative industries

42.5 1.4 35.4 1.8 45.5 1.2 43.6 1.3 41.7 1.4


subsector 2013 2014 2015 2016 average

female share

(%)

m:f ratio

female share

(%)

m:f ratio

female share

(%)

m:f ratio

female share

(%)

m:f ratio

female share

(%)

m:f ratio

Electro-technical

31.0 2.2 31.3 2.2 25.9 2.9 29.5 2.4 29.5 2.4

Film & TV 28.0 2.6 37.9 1.6 32.2 2.1 28.8 2.5 31.7 2.2

ICT services 34.1 1.9 32.5 2.1 35.7 1.8 32.9 2.0 33.8 2.0

Metals 10.7 8.3 11.5 7.7 9.5 9.5 10.6 8.4 10.6 8.4


71.4 0.4 68.3 0.5 66.5 0.5 66.8 0.5 68.3 0.5


Notes: Business processing sector omitted as data on the sector is not available in the LMD Survey data utilised.

Table a 4. Race and gender composition of employment across ssas-eligible subsectors, 2016

subsector african Coloured asian White

female share

(%)

m:f ratio female share

(%)


(%)


(%)

m:f ratio

Agro-processing 28.0 1.5 8.4 1.3 1.1 2.2 2.8 1.4

Automotive 5.5 10.2 1.4 5.4 0.4 18.7 4.6 3.5

Capital equipment 8.4 4.6 2.6 3.0 0.7 5.7 11.9 2.2

Chemical industries 17.8 2.6 6.7 0.7 1.9 1.6 12.3 0.6

Civil engineering 5.0 13.5 0.8 14.8 0.1 18.1 1.9 5.9

Consulting engineers 9.0 4.2 2.0 3.8 1.6 2.2 6.7 4.8

Creative industries 17.0 1.4 15.7 0.8 2.2 5.1 8.7 1.1

Electro-technical 16.7 2.7 5.0 2.0 2.1 0.4 5.7 2.7

Film & TV 13.8 3.5 2.5 3.2 1.6 1.5 11.0 1.1

ICT services 16.2 1.3 3.8 2.1 2.6 2.4 10.3 3.0

Metals 7.1 8.8 0.3 36.4 0.5 4.5 2.8 5.4

Textiles, clothing & leather 47.6 0.5 11.7 0.5 5.3 0.6 2.2 0.5




Table a 5. summary characteristics of firms that received ssas funds

Category share of respondents (%)

Province Western Cape 3.1

Eastern Cape 0.1

Northern Cape 44.4

Free State 13.2

KwaZulu-Natal 2.2

North West 1.2

Gauteng 2.5

Mpumalanga 0.6

Limpopo 32.8

Owners’ race and gender Black male 33.2

Black female 25.5

White male 23.0

White female 18.3

Subsector Agro-processing 9.7

Chemical industries 6.9

Creative industries 44.9

Electro-technical 8.1

Energy 1.5

Metals 7.8

Mining 1.8

Services 2.6

Textiles, clothing & leather 14.8

Multisectoral 2.0

Source: Own calculations based on data provided by the dti (2018).


aPPenDix iv: sURveY of ssas benefiCiaRies

i. owner’s information

1. For each of the business owners, please provide the following information. For ease of reference please refer to the

“Definition” section to obtain a list of options.

name gender Race age nationality Disability status

Highest education

level

Previous Work experience

(in years)

% owner-ship

ii. firm baseline information

2. To which of the following sectors does the firm’s mainly business activity relate? For this questionnaire, the firm’s main

business activity should be the sector that qualified the firm to receive the Sector Specific Assistance Scheme (SSAS)

support. Accordingly, the selected sub-sectors in the “Definition” section correspond to the sectors that are supported by

SSAS.

main business activity Province area

3. Was the business operational for longer than 12 months prior to the application for SSAS support?

4. Prior to the application, did the business engage in export activities?

indicator frequency

Yes

No

Only in some years

5. What is the business’ annual turnover? Kindly provide the actual figures for the year you received SSAS support and also for

the most recent financial year. Alternatively, refer to the “Definition” section to obtain a list of options.

Turnover at time of application Turnover in most recent year

Employee Characteristics

6. To encourage employers to hire young and less experienced work seekers, the government has introduced the Employment

Tax Incentive (ETI). This reduces an employer’s cost of hiring young people by leaving the wage the employee receives

unaffected. Is your business currently utilising this ETI?



7. Do you at present hire workers on a temporary or seasonal basis?

a. If yes, how often and how many?

8. In the table below, kindly indicate the employment characteristics of the firm at the time of application for SSAS support

and in the most recent period post-support.

Pre-application latest period following ssas support

Total number of employees

Gender Males

Females

Race# African

Coloured

Asian

Youth status Youth (aged 15-34 years)

Non-youth (aged 35-64 years)

Working conditions Full time

Part time

Skills levels* Unskilled workers

Semi-skilled workers

Skilled workers

Note: # The definition of Black relates to the BBBEE definition of Black, namely, African, Coloured and Indian/Asian people that are citizens of South Africa by birth or descent or who would have qualified for citizenship before 1994. For further information please refer to:

http://www.dti.gov.za/economic_empowerment/docs/2nd_phase/Code1000Statement1000.pdf

* Please refer to similar definitions as outlined in your latest EEA2 submission.

iii. sector specific assistance scheme

The Sector Specific Assistance Scheme (SSAS) is a reimbursable cost-sharing incentive scheme whereby financial support

is granted to organisations supporting the development of industry sectors and those contributing to the growth of South

African exports. Organisations supported under SSAS include Export Councils, Joint Action Groups, Industry Associations and

those involved in the aimed at the development of emerging exporters.

The Objectives of the Sector Specific Assistance Scheme include:

i. Developing an industry sector as a whole

ii. Developing new export markets

iii. Stimulate job creation

iv. Broadening the export base

v. Proposing solutions to factors inhibiting export growth

vi. Promote broader participation of black owned and SMME’s to the economy. (Source)

Application Process

9. How did your business first hear of SSAS?

10. When did you first apply for SSAS funding?


11. Did the business get support from the dti the first time you applied?

a. If no, what reason did the dti provide you with for the rejection of your application?

12. Was the application process to receive SSAS funding clear and straightforward?

a. If yes, kindly indicate what you most appreciated about the application process.

b. If not, kindly indicate challenges faced and what in your opinion could be done to improve the application

process.

13. Are the SSAS Application Guidelines easy to use, understand and apply?

a. If no, kindly indicate what information needs to be clarified.

14. Did your business apply for generic funding, project funding or project funding for the emerging exporters?

15. Briefly, state your reasons for applying for this specific support from the dti?

16. Was the type of assistance provided by the dti sufficient or not? Please indicate why?

17. Has the business applied for any additional support from the dti?

a. If so, kindly indicate what support this is and whether the application was granted.

18. What type of additional assistance would you have liked to receive, but did not?

19. If doing so would help contribute towards better-designed and more effective interventions/programmes, would you

be willing to give regular feedback on your business’ performance to the dti?

a. If yes, how frequently?

b. If no, why not?

Financial and Non-Financial Impact of the Incentive

20. What, if anything, has been the biggest impact on your business of receiving the support from the dti?

21. To determine the changes to your business following the support from the dti, kindly provide the following information:

Prior to application Post-support

Exports as a share of turnover (%)

Export sales (in R)

Domestic sales (in R)

Share of local procurement purchased from black-owned suppliers (in R)

Share of local procurement purchased from female-owned suppliers (in R)

Share of local procurement purchased from SMME firms (in R)

Did the business have any marketing materials (brochures, pamphlets, CDs or photographs)

Did the business have marketing / product samples?

Did the business have an Export Marketing Plan?

Please only provide these figures post-support

Did attendance at the sponsored event increase your knowledge of your buyers business and cultural context?



Prior to application Post-support

Number of leads arising from the attended event

Number of leads that converted into sales

Value of sales that converted into sales (in R)

Number of new local contacts made

22. Would you characterise your business as profitable at present?

a. Was this the case before you received funding from the dti?

23. Do you currently have plans for expansion?

a. Would you say this is because of the funding you have received?

Engagement with the Project Coordinators

24. Was the assistance you received from the project coordinator during the application process helpful?

a. If yes, please indicate what you found helpful.

b. If no, please indicate what could be improved.

25. What, if any support did you receive from the project coordinator post receiving the SSAS support?

26. What, if any additional support would you have liked to receive from the project coordinator? Please indicate whether

this would be required pre- or post-SSAS support.

The Claim Back Process

27. Was the claim process clear and straightforward?

a. If yes, kindly indicate what you most appreciated about the claim back process.

b. If not, kindly indicate challenges faced and what in your opinion could be done to improve the claim process.

28. Was the full amount claimed by your firm received?

a. If no, please indicate whether you received a reason from the dti as to the shortfall?

29. Where the claim was paid, please indicate how long it took from when the claim was made to when payment was

received.

iv. status of Women

Business Environment

30. What barriers do female entrepreneurs in your sector face from the ideation to implementation stage of establishing a

business?

31. Based on your experience, what types of incentives would encourage more female-owned businesses to apply for support

from the dti?

Application and Support Process

This section applies to female-owned businesses only


32. As a female-owned business, did your entity face any challenges in the application and support process compared to

predominantly male-owned businesses?

a. What could be done to facilitate and improve the experience of women in the process?

33. Did your business apply as an individual firm or as part of a network of firms?

a. Has your business been approached to partner up with other firms (both male- and female-owned) to access

additional support or access markets?

b. If yes, please indicate the impact of this partnership.

c. If you were asked but declined, please indicate why?

Impact of the Incentives

34. Regarding the incentives provided, how have women benefited from the support obtained?

a. Have more women been employed?

b. Has the business concluded more partnerships with or procured from other female-owned businesses?



noTes:

Department of Women, Youth and Persons with Disabilities

36 Hamilton Street

Arcadia

Pretoria

Private Bag X931

Pretoria

0001

South Africa

Tel: +27 12 359 000

Fax: +27 12 326 0473

www.women.gov.za

A GENDER ANALYSIS OF GOVERNMENT’S INCENTIVES SCHEMES ... · Broadening Participation Cluster 45...

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